Integrated Digital System for Yarn Surface Quality Evaluation using Computer Vision and Artificial Intelligence

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Integrated Digital System for Yarn Surface Quality Evaluation using Computer Vision and Artificial Intelligence"

Transcription

1 Integrated Digital System for Yarn Surface Quality Evaluation using Computer Vision and Artificial Intelligence Sheng Yan LI, Jie FENG, Bin Gang XU, and Xiao Ming TAO Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Abstract - The evaluation method of yarn surface quality currently in use is mainly based on manual inspection. In order to resolve the inherent limitations of the human visual inspection, an intelligent evaluation system has been developed for the objective and automatic evaluation of yarn surface quality with computer vision and artificial intelligence. In this system, all yarn surface features are fully digitalized and quantitatively processed to ensure an objective evaluation of yarn surface appearance. This digital system integrates and controls the whole progress of yarn surface analysis, including the image acquisition, digital feature extraction, characteristic parameter computation and yarn quality classification, in one computer program with an interactive and friendly user interface. Besides yarn quality classification, multiple yarn surface characteristics, such as yarn diameter irregularities, yarn fault areas, foreign matters and fuzziness, can also be quantitatively obtained and visibly displayed. Keywords: Yarn evaluation, Intelligent system, Image processing, Artificial neural network 1 Introduction The grade assessment of yarn appearance quality, or so called yarn surface grading, is one of the important testing procedures in the textile industry. According to ASTM D 2255 [1], a standard test method is to wind a yarn sample on a black board using a yarn board winder and then compare the board with a series of photographic standards representing the grades A (best), B, C and D (worst), which assesses yarn surface quality with consideration of the unevenness, fuzziness, neppiness and visible foreign matter. Traditionally, the inspection is carried out by direct observation in which a skilled specialist visually compares the wound yarn sample with the grade labeled photographic standard and then judges the quality of the yarn sample according to the standard definition, as shown in Figure 1. But the method is subjective, time-consuming, and sometimes inconsistent. With the rapid development of computer technology, the image processing and artificial intelligence technologies become more widely used nowadays in textiles. During the past decades, the investigation on digital yarn analysis by using computer vision has attracted an increasing interest of researchers and some valuable research works have been carried out [2-7]. Yarn sample Yarn board winder Human visual observation Figure 1. Traditional method for yarn surface evaluation The paper is an extension of our preliminary work [7] on digital characterization and evaluation of yarn surface appearance. In this paper, we have further developed and implemented an intelligent system for the objective and automatic evaluation of digital yarn appearance quality using computer vision and artificial intelligence. The newly developed system is able to integrate and control the whole progress of yarn surface analysis, including the image acquisition, digital feature extraction, characteristic parameter computation and yarn quality classification, with an interactive and friendly user interface. Besides yarn quality classification, multiple yarn surface characteristics, such as yarn diameter irregularities, yarn fault areas, foreign matters and fuzziness, can also be quantitatively obtained in this system for further study and evaluation. In the following section, the interface and function of the integrated evaluation system for digital yarn appearance quality will be firstly introduced in Section 2. Then, in Section 3, the methodology of the system will be illustrated in details. Finally the conclusions will be given in Section 4.

2 Figure 2. Digital Yarn Surface Grading System 2 Digital and Visible Yarn Surface Grading System 2.1 System Interface and Function The graphics user interface (GUI) of the visible evaluation system for digital yarn appearance quality is shown in Figure 2. In this system, users can carry out the yarn image processing and appearance classification by a series of simple operations, and then the figures and relevant features of the digital yarn image can be displayed visibly. As shown in Figure 3, the main steps of the Digital Yarn Surface Grading System are, firstly, to acquire the yarn image using a commercial scanner, next to load the image into the system, then to conduct the yarn image processing, and finally to classify the yarn appearance grade. Open scanner to obtain yarn image Yarn appearance classification Load scan image into the program Online image processing Figure 3. Main steps of the Digital Yarn Surface Grading System In yarn image processing, the important processing figures and the statistical results of yarn image listed in Table 1 can be computed and shown in the system interface. Besides, the extracted features for yarn appearance classification based on the image processing can also be shown in the input feature frame of the artificial neural network region. Table 1. Visible Results Maps and figures Gray image Binary image Hairiness image Histogram Width map Saliency map Statistical results Value of thick place Value of thin place Value of neps Mean value of diameter Standard deviation of diameter Value of hairiness In addition, the system also provides online help for users, including the user guide (Demo button), flow chat of the program (Flow Chart button) and the digital yarn database for training the artificial neural network (Database button). 2.2 Digital Yarn Database A series of weaving and knitting yarns with different appearance qualities are produced by different spinning methods using different materials and spinning parameters. All these yarn samples are physically measured by Uster Tensorapid for yarn strength, Zweigle hairiness tester for yarn hairiness and Uster III tester for yarn evenness. And the digital yarn images, which are labeled for training the artificial neural network in the yarn surface grading system, are acquired by a scanner. In order to manage the yarn information, a digital yarn database management system is established based on Access database, as shown in Figure 4, which can be started by clicking Database button in the grading system. By

3 retrieving yarn count, yarn appearance grade or the specified ID of yarn samples (see Figure 4 (a)), the physical properties and digital images of yarn can be displayed in the system interface (see Figure 4 (b)). (a) Index and queries interface Figure 6. Original scanned yarn images with different appearance grades 3.2 Image Processing (1) Wavelet transformation for yarn hairiness extraction (b) Detailed information interface Figure 4. Yarn image sample database management system Wavelet transform provides a multi-resolution analysis and is exploited to extract texture characteristics of yarn hairiness. Figure 7 shows identification results of yarn hairiness from the two yarn images. Methodology Image Acquisition In the interface of the intelligent evaluation system, clicking the Scan Yarn Image button on the left top corner can open a scanner for digital yarn image acquisition, with the main steps shown in Figure 5. High image resolution is adopted in digital yarn image acquisition to allow the accurate and consistent evaluation results. Figure 6 shows two scanned images of different grade yarns. These two samples will be used for showing the performance of the methodology in the system when analyzing different grade yarns. Scanner Yarn sample Yarn board winder Figure 5. Yarn image acquisition Computer Figure 7. Hairiness image

4 (2) Fast Fourier transform for yarn diameter segmentation In digital yarn image processing, fast Fourier transform (FFT), Butterworth filters and threshold method are employed to segment yarn diameter from the whole image. Firstly, the scanned color yarn image is transferred to gray image, then changed into frequency domain (FFT) for filtering the hairiness and noise using Butterworth filter. After that an automatic threshold method - Otsu method which chooses the threshold to minimize the interclass variance of the black and white pixels, is used to get the binary image, as shown in Figure x Figure 9. Histogram of yarn diameter Figure 8. Binary image 3.3 Feature Extraction and Classification (1) Yarn diameter statistics Statistical measurement is employed for feature extraction of yarn diameter. Figures 9 to 11 show the histogram, width map and saliency map of yarn diameter. Saliency map [8] is an visual attention method which can topographically identify the visual saliency or distinguished areas of a visual scene by considering the centre-surround contrasts in terms of visual features, including intensity, color and orientations. Here, saliency map is used for yarn fault (abnormal region) detection. Figure 10. Width map of yarn diameter

5 shows the important characteristic results with an interactive and friendly user interface. This computerized technology is potential for commercialization and can be applied in textile testing laboratories and spinning mills for yarn surface quality control and assurance. 5 Acknowledgments The authors wish to acknowledge the funding support from the Hong Kong Polytechnic University for the work reported here. Miss Li SY and Mr Feng J would also thank the Hong Kong Polytechnic University for providing them with postgraduate scholarships. 6 References [1] Standard Test Method for Grading Yarn for Appearance ; ASTM D 2255/D2255M - 09, pp. 1-5, Figure 11. Saliency map based yarn fault detection (2) Artificial neural network for yarn appearance classification In the interface of the developed evaluation system, the Yarn Appearance Classification button is used to employ an artificial neural network to classify and grade yarn surface quality. Based on the above yarn image processing, 18 features including statistical results of yarn diameter and texture characteristics of yarn hairiness, are extracted as input parameters for the artificial neural network. With over 400 training samples in different yarn linear densities (20Ne-80Ne) and appearance grades, the result shows around 87% of over 170 testing samples can be correctly classified by using this artificial neural network [7]. 4 Conclusions A novel integrated intelligent evaluation system was developed to replace the conventional manual inspection for the objective and automatic evaluation of yarn surface appearance with computer vision and artificial intelligence. In the developed system, some recent advances in digital processing and computer science, such as saliency map analysis, wavelet transform and artificial neural network, are developed and incorporated to fully extract the yarn surface characteristic features and then to classify and grade yarn surface qualities based on the digital features. This system integrates the whole progress of yarn surface analysis and [2] D. Semnani, M. Latifi, M.A. Tehran, B. Pourdeyhimi and A.A. Merati. Grading of Yarn Surface Appearance Using Image Analysis and an Artificial Intelligence Technique ; Textile Research Journal, vol. 76, no. 3, pp , [3] X. Zhou. Study on Yarn Blackboard by Digital Image Processing Method ; Modern Applied Science, vol. 1, no. 4, pp , [4] J. Liu, Z. Li, Y. Lu and H. Jiang. Visualisation and Determination of the Geometrical Parameters of Slub Yarn ; FIBRES & TEXTILES in Eastern Europe, vol. 18, no. 1, pp , [5] R. Pan, W. Gao, J. Liu and H. Wang. Recognition the Parameters of Slub-yarn Based on Image Analysis ; Journal of Engineered Fibers and Fabrics, vol. 6, no. 1, pp , [6] H.C. Lien and S. Lee. A Method of Feature Selection for Textile Yarn Grading Using the Effective Distance between Clusters ; Textile Research Journal, vol. 72, no. 10, pp , [7] Z. Liang, B.G. Xu, Z.R. Chi and D.G. Feng. Intelligent Characterization and Evaluation of Yarn Surface Appearance Using Saliency Map Analysis, Wavelet Transform and Fuzzy ARTMAP Neural Network ; Expert Systems with Applications, vol. 39, no. 4, pp , [8] L. Itti, C. Koch and E. Niebur. A Model of Saliency- Based Visual Attention for Rapid Scene Analysis ; IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 11, pp , 1998.

IMAGE TYPE WATER METER CHARACTER RECOGNITION BASED ON EMBEDDED DSP

IMAGE TYPE WATER METER CHARACTER RECOGNITION BASED ON EMBEDDED DSP IMAGE TYPE WATER METER CHARACTER RECOGNITION BASED ON EMBEDDED DSP LIU Ying 1,HAN Yan-bin 2 and ZHANG Yu-lin 3 1 School of Information Science and Engineering, University of Jinan, Jinan 250022, PR China

More information

COLOR IMAGE SEGMENTATION USING K-MEANS CLASSIFICATION ON RGB HISTOGRAM SADIA BASAR, AWAIS ADNAN, NAILA HABIB KHAN, SHAHAB HAIDER

COLOR IMAGE SEGMENTATION USING K-MEANS CLASSIFICATION ON RGB HISTOGRAM SADIA BASAR, AWAIS ADNAN, NAILA HABIB KHAN, SHAHAB HAIDER COLOR IMAGE SEGMENTATION USING K-MEANS CLASSIFICATION ON RGB HISTOGRAM SADIA BASAR, AWAIS ADNAN, NAILA HABIB KHAN, SHAHAB HAIDER Department of Computer Science, Institute of Management Sciences, 1-A, Sector

More information

Uster Technologies (Suzhou) Co.Ltd., Textile Laboratory Testing Services

Uster Technologies (Suzhou) Co.Ltd., Textile Laboratory Testing Services Uster Technologies (Suzhou) Co.Ltd., Textile Laboratory Testing Services 1. Test items Textile testing on fibers 1 2 USTER HVI 1000 Bundle fiber testing Determination of fiber fineness, maturity index,

More information

Content Based Image Retrieval Using Color Histogram

Content Based Image Retrieval Using Color Histogram Content Based Image Retrieval Using Color Histogram Nitin Jain Assistant Professor, Lokmanya Tilak College of Engineering, Navi Mumbai, India. Dr. S. S. Salankar Professor, G.H. Raisoni College of Engineering,

More information

USTER ZWEIGLE TWIST TESTER 5

USTER ZWEIGLE TWIST TESTER 5 USTER ZWEIGLE TWIST TESTER 5 APPLICATION REPORT Measurement and significance of yarn twist THE YARN PROCESS CONTROL SYSTEM R. Furter, S. Meier September 2009 SE 631 Copyright 2009 by Uster Technologies

More information

APPLICATION REPORT QUALITY MANAGEMENT. The standardization of quality characteristics in the textile supply chain THE STANDARD FROM FIBER TO FABRIC

APPLICATION REPORT QUALITY MANAGEMENT. The standardization of quality characteristics in the textile supply chain THE STANDARD FROM FIBER TO FABRIC APPLICATION REPORT QUALITY MANAGEMENT The standardization of quality characteristics in the textile supply chain THE STANDARD FROM FIBER TO FABRIC R. Furter October 2009 SE 634 Copyright 2009 by Uster

More information

Digital Jacquard Textile Design In A Colorless Mode

Digital Jacquard Textile Design In A Colorless Mode Digital Jacquard Textile Design In A Colorless Mode NG, Frankie M.C. and ZHOU, Jiu Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hong Kong. ABSTRACT Jacquard fabric is regarded

More information

USTER STATISTICS 2013

USTER STATISTICS 2013 USTER STATISTICS 2013 Application Report Easy User Guide Copyright 2013 by Uster Technologies AG All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, translated

More information

OPEN-END YARN PROPERTIES PREDICTION USING HVI FIBRE PROPERTIES AND PROCESS PARAMETERS

OPEN-END YARN PROPERTIES PREDICTION USING HVI FIBRE PROPERTIES AND PROCESS PARAMETERS OPEN-END YARN PROPERTIES PREDICTION USING HVI FIBRE PROPERTIES AND PROCESS PARAMETERS Hanen Ghanmi 1,2, Adel Ghith 2,3, Tarek Benameur 1 1 University of Monastir, National Engineering School, Laboratory

More information

Automatic Defect Detection Algorithm for Woven Fabric using Artificial Neural Network Techniques

Automatic Defect Detection Algorithm for Woven Fabric using Artificial Neural Network Techniques Automatic Defect Detection Algorithm for Woven Fabric using Artificial Neural Network Techniques Dr. G. M. Nasira 1, P.Banumathi 2 Assistant. Professor, Department of Computer Science and Applications,

More information

Influence of production technology on the cotton yarn properties

Influence of production technology on the cotton yarn properties Influence of production technology on the cotton yarn properties Dana Kremenakova and Jiri Militky Technical University of Liberec, Textile Faculty, Research Center Textile, Liberec 463 11, CZECH REPUBLIC

More information

Automatic Locating the Centromere on Human Chromosome Pictures

Automatic Locating the Centromere on Human Chromosome Pictures Automatic Locating the Centromere on Human Chromosome Pictures M. Moradi Electrical and Computer Engineering Department, Faculty of Engineering, University of Tehran, Tehran, Iran moradi@iranbme.net S.

More information

ROBOT VISION. Dr.M.Madhavi, MED, MVSREC

ROBOT VISION. Dr.M.Madhavi, MED, MVSREC ROBOT VISION Dr.M.Madhavi, MED, MVSREC Robotic vision may be defined as the process of acquiring and extracting information from images of 3-D world. Robotic vision is primarily targeted at manipulation

More information

Color Image Segmentation Using K-Means Clustering and Otsu s Adaptive Thresholding

Color Image Segmentation Using K-Means Clustering and Otsu s Adaptive Thresholding Color Image Segmentation Using K-Means Clustering and Otsu s Adaptive Thresholding Vijay Jumb, Mandar Sohani, Avinash Shrivas Abstract In this paper, an approach for color image segmentation is presented.

More information

Weaving Density Evaluation with the Aid of Image Analysis

Weaving Density Evaluation with the Aid of Image Analysis Lenka Techniková, Maroš Tunák Faculty of Textile Engineering, Technical University of Liberec, Studentská, 46 7 Liberec, Czech Republic, E-mail: lenka.technikova@tul.cz. maros.tunak@tul.cz. Weaving Density

More information

COLOR LASER PRINTER IDENTIFICATION USING PHOTOGRAPHED HALFTONE IMAGES. Do-Guk Kim, Heung-Kyu Lee

COLOR LASER PRINTER IDENTIFICATION USING PHOTOGRAPHED HALFTONE IMAGES. Do-Guk Kim, Heung-Kyu Lee COLOR LASER PRINTER IDENTIFICATION USING PHOTOGRAPHED HALFTONE IMAGES Do-Guk Kim, Heung-Kyu Lee Graduate School of Information Security, KAIST Department of Computer Science, KAIST ABSTRACT Due to the

More information

u TESTER 6 The Total Testing Center

u TESTER 6 The Total Testing Center u TESTER 6 The Total Testing Center What is Think Quality? It is managing your spinning mill with quality in mind. In today s competitive markets, spinning mills need to deliver yarn of the right quality

More information

THE detection of defects in road surfaces is necessary

THE detection of defects in road surfaces is necessary Author manuscript, published in "Electrotechnical Conference, The 14th IEEE Mediterranean, AJACCIO : France (2008)" Detection of Defects in Road Surface by a Vision System N. T. Sy M. Avila, S. Begot and

More information

An Efficient Method for Landscape Image Classification and Matching Based on MPEG-7 Descriptors

An Efficient Method for Landscape Image Classification and Matching Based on MPEG-7 Descriptors An Efficient Method for Landscape Image Classification and Matching Based on MPEG-7 Descriptors Pharindra Kumar Sharma Nishchol Mishra M.Tech(CTA), SOIT Asst. Professor SOIT, RajivGandhi Technical University,

More information

Method to acquire regions of fruit, branch and leaf from image of red apple in orchard

Method to acquire regions of fruit, branch and leaf from image of red apple in orchard Modern Physics Letters B Vol. 31, Nos. 19 21 (2017) 1740039 (7 pages) c World Scientific Publishing Company DOI: 10.1142/S0217984917400395 Method to acquire regions of fruit, branch and leaf from image

More information

Influence of yarn count, yarn twist and yarn technology production on yarn hairiness

Influence of yarn count, yarn twist and yarn technology production on yarn hairiness Influence of yarn count, yarn twist and yarn technology production on yarn hairiness KRUPINCOVÁ Gabriela Department of Textile Technology, Technical University of Liberec, Liberec 461 17, Czech Republic

More information

2 Human Visual Characteristics

2 Human Visual Characteristics 3rd International Conference on Multimedia Technology(ICMT 2013) Study on new gray transformation of infrared image based on visual property Shaosheng DAI 1, Xingfu LI 2, Zhihui DU 3, Bin ZhANG 4 and Xinlin

More information

Adaptive Feature Analysis Based SAR Image Classification

Adaptive Feature Analysis Based SAR Image Classification I J C T A, 10(9), 2017, pp. 973-977 International Science Press ISSN: 0974-5572 Adaptive Feature Analysis Based SAR Image Classification Debabrata Samanta*, Abul Hasnat** and Mousumi Paul*** ABSTRACT SAR

More information

Published by: PIONEER RESEARCH & DEVELOPMENT GROUP (www.prdg.org) 1

Published by: PIONEER RESEARCH & DEVELOPMENT GROUP (www.prdg.org) 1 IJREAT International Journal of Research in Engineering & Advanced Technology, Volume 2, Issue 2, Apr- Generating an Iris Code Using Iris Recognition for Biometric Application S.Banurekha 1, V.Manisha

More information

yarnmaster digital online Quality Control

yarnmaster digital online Quality Control Masters in Textile textile Quality Control yarnmaster digital online Quality Control facts Classification of Yarn Faults and Splices 045912/003e Classification of Yarn Faults yarnmaster digital online

More information

CHAPTER - 2 RING & COMPACT YARN TECHNOLOGY

CHAPTER - 2 RING & COMPACT YARN TECHNOLOGY CHAPTER - 2 RING & COMPACT YARN TECHNOLOGY 2.1 Introduction Several Researchers have shown that compact yarn have greater evenness of structure and reduced hairiness as compared to ring yarn. Artz [135]

More information

License Plate Localisation based on Morphological Operations

License Plate Localisation based on Morphological Operations License Plate Localisation based on Morphological Operations Xiaojun Zhai, Faycal Benssali and Soodamani Ramalingam School of Engineering & Technology University of Hertfordshire, UH Hatfield, UK Abstract

More information

Effect of light intensity on Epinephelus malabaricus s image processing Su Xu 1,a, Kezhi Xing 1,2,*, Yunchen Tian 3,* and Guoqiang Ma 3

Effect of light intensity on Epinephelus malabaricus s image processing Su Xu 1,a, Kezhi Xing 1,2,*, Yunchen Tian 3,* and Guoqiang Ma 3 2nd International Conference on Electrical, Computer Engineering and Electronics (ICECEE 2015) Effect of light intensity on Epinephelus malabaricus s image processing Su Xu 1,a, Kezhi Xing 1,2,*, Yunchen

More information

Automatic Crack Detection on Pressed panels using camera image Processing

Automatic Crack Detection on Pressed panels using camera image Processing 8th European Workshop On Structural Health Monitoring (EWSHM 2016), 5-8 July 2016, Spain, Bilbao www.ndt.net/app.ewshm2016 Automatic Crack Detection on Pressed panels using camera image Processing More

More information

A Method of Multi-License Plate Location in Road Bayonet Image

A Method of Multi-License Plate Location in Road Bayonet Image A Method of Multi-License Plate Location in Road Bayonet Image Ying Qian The lab of Graphics and Multimedia Chongqing University of Posts and Telecommunications Chongqing, China Zhi Li The lab of Graphics

More information

Contrast adaptive binarization of low quality document images

Contrast adaptive binarization of low quality document images Contrast adaptive binarization of low quality document images Meng-Ling Feng a) and Yap-Peng Tan b) School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, Singapore

More information

USTER TESTER 5-S800. The yarn inspection system. Technical Data

USTER TESTER 5-S800. The yarn inspection system. Technical Data USTER TESTER 5-S800 The yarn inspection system Technical Data February 2014 Testing and analyzing installation for the quality assurance of yarn, roving and sliver of staple fibers Elements of the USTER

More information

Optimisation of Cotton Fibre Blends using AI Machine Learning Techniques

Optimisation of Cotton Fibre Blends using AI Machine Learning Techniques Optimisation of Cotton Fibre Blends using AI Machine Learning Techniques ZORAN STJEPANOVIC, ANTON JEZERNIK Department of Textiles, Faculty of Mechanical Engineering University of Maribor Smetanova 17,

More information

Live Hand Gesture Recognition using an Android Device

Live Hand Gesture Recognition using an Android Device Live Hand Gesture Recognition using an Android Device Mr. Yogesh B. Dongare Department of Computer Engineering. G.H.Raisoni College of Engineering and Management, Ahmednagar. Email- yogesh.dongare05@gmail.com

More information

BLENDING BEHAVIOR OF COTTON AND POLYESTER FIBERS ON DIFFERENT SPINNING SYSTEMS IN RELATION TO PHYSICAL PROPERTIES OF BLENDED YARNS

BLENDING BEHAVIOR OF COTTON AND POLYESTER FIBERS ON DIFFERENT SPINNING SYSTEMS IN RELATION TO PHYSICAL PROPERTIES OF BLENDED YARNS 1 BLENDING BEHAVIOR OF COTTON AND POLYESTER FIBERS ON DIFFERENT SPINNING SYSTEMS IN RELATION TO PHYSICAL PROPERTIES OF BLENDED YARNS Ghada Ali Abou-Nassif Fashion Design Department, Design and Art Faculty,

More information

THE WAY TO THINK QUALITY

THE WAY TO THINK QUALITY RANDOM TESTING IS THE PAST TOTAL TESTING IS THE FUTURE! WITH ONLINE AND OFF-LINE SOLUTIONS THIS IS NOW A REALITY! THE WAY TO THINK QUALITY 240 840-11020/8.07/ Copyright 2007 Uster Technologies AG The 5

More information

AN APPROXIMATION-WEIGHTED DETAIL CONTRAST ENHANCEMENT FILTER FOR LESION DETECTION ON MAMMOGRAMS

AN APPROXIMATION-WEIGHTED DETAIL CONTRAST ENHANCEMENT FILTER FOR LESION DETECTION ON MAMMOGRAMS AN APPROXIMATION-WEIGHTED DETAIL CONTRAST ENHANCEMENT FILTER FOR LESION DETECTION ON MAMMOGRAMS Zhuangzhi Yan, Xuan He, Shupeng Liu, and Donghui Lu Department of Biomedical Engineering, Shanghai University,

More information

CHARACTERISTICS OF COTTON FABRICS PRODUCED FROM SIROSPUN AND PLIED YARNS

CHARACTERISTICS OF COTTON FABRICS PRODUCED FROM SIROSPUN AND PLIED YARNS Egypt. J. Agric. Res., 89 (2), 2011 579 CHARACTERISTICS OF COTTON FABRICS PRODUCED FROM SIROSPUN AND PLIED YARNS Cotton Research Institute, ARC, Giza EL-SAYED, M. A. M. AND SUZAN H. SANAD (Manuscript received

More information

Fingerprint Image Enhancement via Raised Cosine Filtering

Fingerprint Image Enhancement via Raised Cosine Filtering Fingerprint Image Enhancement via Raised Cosine Filtering Shing Chyi Chua 1a, Eng Kiong Wong 2, Alan Wee Chiat Tan 3 1,2,3 Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia.

More information

AUTOMATED MALARIA PARASITE DETECTION BASED ON IMAGE PROCESSING PROJECT REFERENCE NO.: 38S1511

AUTOMATED MALARIA PARASITE DETECTION BASED ON IMAGE PROCESSING PROJECT REFERENCE NO.: 38S1511 AUTOMATED MALARIA PARASITE DETECTION BASED ON IMAGE PROCESSING PROJECT REFERENCE NO.: 38S1511 COLLEGE : BANGALORE INSTITUTE OF TECHNOLOGY, BENGALURU BRANCH : COMPUTER SCIENCE AND ENGINEERING GUIDE : DR.

More information

Intelligent Identification System Research

Intelligent Identification System Research 2016 International Conference on Manufacturing Construction and Energy Engineering (MCEE) ISBN: 978-1-60595-374-8 Intelligent Identification System Research Zi-Min Wang and Bai-Qing He Abstract: From the

More information

Selection of appropriate ring traveller number for different count of cotton hosiery yarn

Selection of appropriate ring traveller number for different count of cotton hosiery yarn International Journal of Engineering & Technology IJET-IJENS Vol: 11 No: 06 70 Selection of appropriate ring traveller number for different count of cotton hosiery yarn 1 Jamal Hossen, 2 Subrata Kumar

More information

Vehicle Number Plate Recognition with Bilinear Interpolation and Plotting Horizontal and Vertical Edge Processing Histogram with Sound Signals

Vehicle Number Plate Recognition with Bilinear Interpolation and Plotting Horizontal and Vertical Edge Processing Histogram with Sound Signals Vehicle Number Plate Recognition with Bilinear Interpolation and Plotting Horizontal and Vertical Edge Processing Histogram with Sound Signals Aarti 1, Dr. Neetu Sharma 2 1 DEPArtment Of Computer Science

More information

Using Linear Mean and Variance Technique to Evaluate the Patterning in Random Winding Process

Using Linear Mean and Variance Technique to Evaluate the Patterning in Random Winding Process JOURNAL OF TEXTILES AND POLYMERS, VOL. 3, NO. 1, JANUARY 2015 1 Using Linear Mean and Variance Technique to Evaluate the Patterning in Random Winding Process Rasoul Mahdi, Mohammad Sheikhzadeh, Dariush

More information

Segmentation of Microscopic Bone Images

Segmentation of Microscopic Bone Images International Journal of Electronics Engineering, 2(1), 2010, pp. 11-15 Segmentation of Microscopic Bone Images Anand Jatti Research Scholar, Vishveshvaraiah Technological University, Belgaum, Karnataka

More information

Automated Visual Inspection: Position Identification of Object for Industrial Robot Application based on Color and Shape

Automated Visual Inspection: Position Identification of Object for Industrial Robot Application based on Color and Shape I.J. Intelligent Systems and Applications, 2016, 1, 9-17 Published Online January 2016 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijisa.2016.01.02 Automated Visual Inspection: Position Identification

More information

DESIGN & DEVELOPMENT OF COLOR MATCHING ALGORITHM FOR IMAGE RETRIEVAL USING HISTOGRAM AND SEGMENTATION TECHNIQUES

DESIGN & DEVELOPMENT OF COLOR MATCHING ALGORITHM FOR IMAGE RETRIEVAL USING HISTOGRAM AND SEGMENTATION TECHNIQUES International Journal of Information Technology and Knowledge Management July-December 2011, Volume 4, No. 2, pp. 585-589 DESIGN & DEVELOPMENT OF COLOR MATCHING ALGORITHM FOR IMAGE RETRIEVAL USING HISTOGRAM

More information

A new technique for distance measurement of between vehicles to vehicles by plate car using image processing

A new technique for distance measurement of between vehicles to vehicles by plate car using image processing Available online at www.sciencedirect.com Procedia Engineering 32 (2012) 348 353 I-SEEC2011 A new technique for distance measurement of between vehicles to vehicles by plate car using image processing

More information

USTER STATISTICS Application Report

USTER STATISTICS Application Report 3 USTER STATISTICS Application Report The common quality language for the textile industry Textile Technology / December 2012 / SE-668 Editorial team Thomas Nasiou Gabriela Peters Review team Dr. Geoffrey

More information

Online Control of Knitted Fabric Quality: Loop Length Control

Online Control of Knitted Fabric Quality: Loop Length Control Online Control of Knitted Fabric Quality: Loop Length Control Dariush Semnani, and Mohammad Sheikhzadeh Abstract Circular knitting machine makes the fabric with more than two knitting tools. Variation

More information

A NOVEL APPROACH FOR CHARACTER RECOGNITION OF VEHICLE NUMBER PLATES USING CLASSIFICATION

A NOVEL APPROACH FOR CHARACTER RECOGNITION OF VEHICLE NUMBER PLATES USING CLASSIFICATION A NOVEL APPROACH FOR CHARACTER RECOGNITION OF VEHICLE NUMBER PLATES USING CLASSIFICATION Nora Naik Assistant Professor, Dept. of Computer Engineering, Agnel Institute of Technology & Design, Goa, India

More information

An Efficient Color Image Segmentation using Edge Detection and Thresholding Methods

An Efficient Color Image Segmentation using Edge Detection and Thresholding Methods 19 An Efficient Color Image Segmentation using Edge Detection and Thresholding Methods T.Arunachalam* Post Graduate Student, P.G. Dept. of Computer Science, Govt Arts College, Melur - 625 106 Email-Arunac682@gmail.com

More information

An Approach for Reconstructed Color Image Segmentation using Edge Detection and Threshold Methods

An Approach for Reconstructed Color Image Segmentation using Edge Detection and Threshold Methods An Approach for Reconstructed Color Image Segmentation using Edge Detection and Threshold Methods Mohd. Junedul Haque, Sultan H. Aljahdali College of Computers and Information Technology Taif University

More information

A Real Time based Image Segmentation Technique to Identify Rotten Pointed Gourds Pratikshya Mohanty, Avinash Kranti Pradhan, Shreetam Behera

A Real Time based Image Segmentation Technique to Identify Rotten Pointed Gourds Pratikshya Mohanty, Avinash Kranti Pradhan, Shreetam Behera A Real Time based Image Segmentation Technique to Identify Rotten Pointed Gourds Pratikshya Mohanty, Avinash Kranti Pradhan, Shreetam Behera Abstract Every object can be identified based on its physical

More information

Comparison of the results of different hairiness testers for cotton-tencel blended ring, compact and vortex yarns a

Comparison of the results of different hairiness testers for cotton-tencel blended ring, compact and vortex yarns a Indian Journal of Fibre & Textile Research Vol. 39, March 204, pp. 4954 Comparison of the results of different hairiness testers for cottontencel blended ring, compact and vortex yarns a Musa Kilic b &

More information

Application of Machine Vision Technology in the Diagnosis of Maize Disease

Application of Machine Vision Technology in the Diagnosis of Maize Disease Application of Machine Vision Technology in the Diagnosis of Maize Disease Liying Cao, Xiaohui San, Yueling Zhao, and Guifen Chen * College of Information and Technology Science, Jilin Agricultural University,

More information

Combined Approach for Face Detection, Eye Region Detection and Eye State Analysis- Extended Paper

Combined Approach for Face Detection, Eye Region Detection and Eye State Analysis- Extended Paper International Journal of Engineering Research and Development e-issn: 2278-067X, p-issn: 2278-800X, www.ijerd.com Volume 10, Issue 9 (September 2014), PP.57-68 Combined Approach for Face Detection, Eye

More information

The Study on the Image Thresholding Segmentation Algorithm. Yue Liu, Jia-mei Xue *, Hua Li

The Study on the Image Thresholding Segmentation Algorithm. Yue Liu, Jia-mei Xue *, Hua Li International Conference on Intelligent Systems Research and Mechatronics Engineering (ISRME 2015) The Study on the Image Thresholding Segmentation Algorithm Yue Liu, Jia-mei Xue *, Hua Li College of Information

More information

FAULT DETECTION AND DIAGNOSIS OF HIGH SPEED SWITCHING DEVICES IN POWER INVERTER

FAULT DETECTION AND DIAGNOSIS OF HIGH SPEED SWITCHING DEVICES IN POWER INVERTER FAULT DETECTION AND DIAGNOSIS OF HIGH SPEED SWITCHING DEVICES IN POWER INVERTER R. B. Dhumale 1, S. D. Lokhande 2, N. D. Thombare 3, M. P. Ghatule 4 1 Department of Electronics and Telecommunication Engineering,

More information

Student Attendance Monitoring System Via Face Detection and Recognition System

Student Attendance Monitoring System Via Face Detection and Recognition System IJSTE - International Journal of Science Technology & Engineering Volume 2 Issue 11 May 2016 ISSN (online): 2349-784X Student Attendance Monitoring System Via Face Detection and Recognition System Pinal

More information

Road Network Extraction and Recognition Using Color

Road Network Extraction and Recognition Using Color Road Network Extraction and Recognition Using Color Clustering From Color Map Images Zhang Lulu 1, He Ning,Xu Cheng 3 Beijing Key Laboratory of Information Service Engineer Information Institute,Beijing

More information

Geometric Feature Extraction of Selected Rice Grains using Image Processing Techniques

Geometric Feature Extraction of Selected Rice Grains using Image Processing Techniques Geometric Feature Extraction of Selected Rice Grains using Image Processing Techniques Sukhvir Kaur School of Electrical Engg. & IT COAE&T, PAU Ludhiana, India Derminder Singh School of Electrical Engg.

More information

AUTOMATED PAVEMENT IMAGING PROGRAM (APIP) FOR PAVEMENT CRACKS CLASSIFICATION AND QUANTIFICATION A PHOTOGRAMMETRIC APPROACH

AUTOMATED PAVEMENT IMAGING PROGRAM (APIP) FOR PAVEMENT CRACKS CLASSIFICATION AND QUANTIFICATION A PHOTOGRAMMETRIC APPROACH AUTOMATED PAVEMENT IMAGING PROGRAM (APIP) FOR PAVEMENT CRACKS CLASSIFICATION AND QUANTIFICATION A PHOTOGRAMMETRIC APPROACH M. Mustaffar a*, T. C. Ling b, O. C. Puan b a Surveying Unit, Faculty of Civil

More information

Wavelet-Based Multiresolution Matching for Content-Based Image Retrieval

Wavelet-Based Multiresolution Matching for Content-Based Image Retrieval Wavelet-Based Multiresolution Matching for Content-Based Image Retrieval Te-Wei Chiang 1 Tienwei Tsai 2 Yo-Ping Huang 2 1 Department of Information Networing Technology, Chihlee Institute of Technology,

More information

Recent Progress on Mechanical Condition Monitoring and Fault diagnosis

Recent Progress on Mechanical Condition Monitoring and Fault diagnosis Available online at www.sciencedirect.com Procedia Engineering 15 (2011) 142 146 Advanced in Control Engineeringand Information Science Recent Progress on Mechanical Condition Monitoring and Fault diagnosis

More information

Geometrical parameters of yarn cross-section in plain woven fabric

Geometrical parameters of yarn cross-section in plain woven fabric Indian Journal of Fibre & Textile Research Vol. 38, June 2013, pp. 126-131 Geometrical parameters of yarn cross-section in plain woven fabric Siavash Afrashteh 1,a, Ali Akbar Merati 2 & Ali Asghar Asgharian

More information

Demonstrate knowledge of woollen carding and spinning technology

Demonstrate knowledge of woollen carding and spinning technology Page 1 of 5 Demonstrate knowledge of woollen carding and spinning technology Level 5 Credits 20 Purpose People credited with this unit standard are able to demonstrate knowledge of: the nature and use

More information

The Classification of Gun s Type Using Image Recognition Theory

The Classification of Gun s Type Using Image Recognition Theory International Journal of Information and Electronics Engineering, Vol. 4, No. 1, January 214 The Classification of s Type Using Image Recognition Theory M. L. Kulthon Kasemsan Abstract The research aims

More information

Influence of Spindle Air Pressure and Its Direction on the Quality Characteristics of Polyester/Cotton Vortex Yarn

Influence of Spindle Air Pressure and Its Direction on the Quality Characteristics of Polyester/Cotton Vortex Yarn Influence of Spindle Air Pressure and Its Direction on the Quality Characteristics of Polyester/Cotton Vortex Yarn Sankara Kuthalam, Senthikumar P. Anna University, PSG College of Technology, Coimbatore,

More information

YarN master ZENIT en

YarN master ZENIT en 45919003en yarnmaster zenit Built to see more ZENIT The decisive factors are: With the new YarnMaster Zenit generation LOEPFE succeeded in raising the reliable technology of optical yarn clearers to a

More information

VEHICLE LICENSE PLATE DETECTION ALGORITHM BASED ON STATISTICAL CHARACTERISTICS IN HSI COLOR MODEL

VEHICLE LICENSE PLATE DETECTION ALGORITHM BASED ON STATISTICAL CHARACTERISTICS IN HSI COLOR MODEL VEHICLE LICENSE PLATE DETECTION ALGORITHM BASED ON STATISTICAL CHARACTERISTICS IN HSI COLOR MODEL Instructor : Dr. K. R. Rao Presented by: Prasanna Venkatesh Palani (1000660520) prasannaven.palani@mavs.uta.edu

More information

Journal of Asian Scientific Research IMPROVEMENT OF PEST DETECTION USING HISTOGRAM ADJUSTMENT METHOD AND GABOR WAVELET

Journal of Asian Scientific Research IMPROVEMENT OF PEST DETECTION USING HISTOGRAM ADJUSTMENT METHOD AND GABOR WAVELET Journal of Asian Scientific Research ISSN(e): 2223-1331/ISSN(p): 2226-5724 URL: www.aessweb.com IMPROVEMENT OF PEST DETECTION USING HISTOGRAM ADJUSTMENT METHOD AND GABOR WAVELET Mostafa Bayat 1 --- Mahdi

More information

Estimating malaria parasitaemia in images of thin smear of human blood

Estimating malaria parasitaemia in images of thin smear of human blood CSIT (March 2014) 2(1):43 48 DOI 10.1007/s40012-014-0043-7 Estimating malaria parasitaemia in images of thin smear of human blood Somen Ghosh Ajay Ghosh Sudip Kundu Received: 3 April 2014 / Accepted: 4

More information

Linear Gaussian Method to Detect Blurry Digital Images using SIFT

Linear Gaussian Method to Detect Blurry Digital Images using SIFT IJCAES ISSN: 2231-4946 Volume III, Special Issue, November 2013 International Journal of Computer Applications in Engineering Sciences Special Issue on Emerging Research Areas in Computing(ERAC) www.caesjournals.org

More information

Method for Real Time Text Extraction of Digital Manga Comic

Method for Real Time Text Extraction of Digital Manga Comic Method for Real Time Text Extraction of Digital Manga Comic Kohei Arai Information Science Department Saga University Saga, 840-0027, Japan Herman Tolle Software Engineering Department Brawijaya University

More information

Hybrid Segmentation Approach and Preprocessing of Color Image based on Haar Wavelet Transform

Hybrid Segmentation Approach and Preprocessing of Color Image based on Haar Wavelet Transform Hybrid Segmentation Approach and Preprocessing of Color Image based on Haar Wavelet Transform Reena Thakur Anand Engineering College, Agra, India Arun Yadav Hindustan Institute of Technology andmanagement,

More information

Image Smoothening and Sharpening using Frequency Domain Filtering Technique

Image Smoothening and Sharpening using Frequency Domain Filtering Technique Volume 5, Issue 4, April (17) Image Smoothening and Sharpening using Frequency Domain Filtering Technique Swati Dewangan M.Tech. Scholar, Computer Networks, Bhilai Institute of Technology, Durg, India.

More information

Estimation of Debonded Area in Bearing Babbitt Metal by C-Scan Method

Estimation of Debonded Area in Bearing Babbitt Metal by C-Scan Method ECNDT 2006 - Poster 163 Estimation of Debonded Area in Bearing Babbitt Metal by C-Scan Method Gye-jo JUNG, Sang-ki PARK, Korea Electric Power Research Institute, Yu-sung, Taejeon, Korea, Seok-ju CHA, GEN

More information

International Journal of Engineering & Technology IJET-IJENS Vol: 11 No: 06 75

International Journal of Engineering & Technology IJET-IJENS Vol: 11 No: 06 75 International Journal of Engineering & Technology IJET-IJENS Vol: 11 No: 06 75 Optimization of Doubling at Draw Frame for Quality of Carded Ring Yarn A. Subrata Kumar Saha, B. Jamal Hossen Lecturer, Department

More information

A Method of Using Digital Image Processing for Edge Detection of Red Blood Cells

A Method of Using Digital Image Processing for Edge Detection of Red Blood Cells Sensors & Transducers 013 by IFSA http://www.sensorsportal.com A Method of Using Digital Image Processing for Edge Detection of Red Blood Cells 1 Jinping LI, Hongshan MU, Wei XU 1 Software School, East

More information

Real Time Video Analysis using Smart Phone Camera for Stroboscopic Image

Real Time Video Analysis using Smart Phone Camera for Stroboscopic Image Real Time Video Analysis using Smart Phone Camera for Stroboscopic Image Somnath Mukherjee, Kritikal Solutions Pvt. Ltd. (India); Soumyajit Ganguly, International Institute of Information Technology (India)

More information

A Proficient Matching For Iris Segmentation and Recognition Using Filtering Technique

A Proficient Matching For Iris Segmentation and Recognition Using Filtering Technique A Proficient Matching For Iris Segmentation and Recognition Using Filtering Technique Ms. Priti V. Dable 1, Prof. P.R. Lakhe 2, Mr. S.S. Kemekar 3 Ms. Priti V. Dable 1 (PG Scholar) Comm (Electronics) S.D.C.E.

More information

Malaysian Car Number Plate Detection System Based on Template Matching and Colour Information

Malaysian Car Number Plate Detection System Based on Template Matching and Colour Information Malaysian Car Number Plate Detection System Based on Template Matching and Colour Information Mohd Firdaus Zakaria, Shahrel A. Suandi Intelligent Biometric Group, School of Electrical and Electronics Engineering,

More information

High-speed Micro-crack Detection of Solar Wafers with Variable Thickness

High-speed Micro-crack Detection of Solar Wafers with Variable Thickness High-speed Micro-crack Detection of Solar Wafers with Variable Thickness T. W. Teo, Z. Mahdavipour, M. Z. Abdullah School of Electrical and Electronic Engineering Engineering Campus Universiti Sains Malaysia

More information

USTER ZWEIGLE TWIST TESTER 5

USTER ZWEIGLE TWIST TESTER 5 USTER ZWEIGLE TWIST TESTER 5 APPLICATION REPORT USTER STATISTICS for twist measurement THE YARN PROCESS CONTROL SYSTEM Sandra Meier July 2009 SE 632 Copyright 2009 by Uster Technologies AG All rights reserved.

More information

Advanced Maximal Similarity Based Region Merging By User Interactions

Advanced Maximal Similarity Based Region Merging By User Interactions Advanced Maximal Similarity Based Region Merging By User Interactions Nehaverma, Deepak Sharma ABSTRACT Image segmentation is a popular method for dividing the image into various segments so as to change

More information

Automatic Counterfeit Protection System Code Classification

Automatic Counterfeit Protection System Code Classification Automatic Counterfeit Protection System Code Classification Joost van Beusekom a,b, Marco Schreyer a, Thomas M. Breuel b a German Research Center for Artificial Intelligence (DFKI) GmbH D-67663 Kaiserslautern,

More information

A Novel Approach of Compressing Images and Assessment on Quality with Scaling Factor

A Novel Approach of Compressing Images and Assessment on Quality with Scaling Factor A Novel Approach of Compressing Images and Assessment on Quality with Scaling Factor Umesh 1,Mr. Suraj Rana 2 1 M.Tech Student, 2 Associate Professor (ECE) Department of Electronic and Communication Engineering

More information

A Novel Curvelet Based Image Denoising Technique For QR Codes

A Novel Curvelet Based Image Denoising Technique For QR Codes A Novel Curvelet Based Image Denoising Technique For QR Codes 1 KAUSER ANJUM 2 DR CHANNAPPA BHYARI 1 Research Scholar, Shri Jagdish Prasad Jhabarmal Tibrewal University,JhunJhunu,Rajasthan India Assistant

More information

NON UNIFORM BACKGROUND REMOVAL FOR PARTICLE ANALYSIS BASED ON MORPHOLOGICAL STRUCTURING ELEMENT:

NON UNIFORM BACKGROUND REMOVAL FOR PARTICLE ANALYSIS BASED ON MORPHOLOGICAL STRUCTURING ELEMENT: IJCE January-June 2012, Volume 4, Number 1 pp. 59 67 NON UNIFORM BACKGROUND REMOVAL FOR PARTICLE ANALYSIS BASED ON MORPHOLOGICAL STRUCTURING ELEMENT: A COMPARATIVE STUDY Prabhdeep Singh1 & A. K. Garg2

More information

A QR Code Image Recognition Method for an Embedded Access Control System Zhe DONG 1, Feng PAN 1,*, Chao PAN 2, and Bo-yang XING 1

A QR Code Image Recognition Method for an Embedded Access Control System Zhe DONG 1, Feng PAN 1,*, Chao PAN 2, and Bo-yang XING 1 2016 International Conference on Mathematical, Computational and Statistical Sciences and Engineering (MCSSE 2016) ISBN: 978-1-60595-396-0 A QR Code Image Recognition Method for an Embedded Access Control

More information

Image Retrieval of Digital Crime Scene Images

Image Retrieval of Digital Crime Scene Images FORENSIC SCIENCE JOURNAL SINCE 2002 Forensic Science Journal 2005;4:37-45 Image Retrieval of Digital Crime Scene Images Che-Yen Wen, 1,* Ph.D. ; Chiu-Chung Yu, 1 M.S. 1 Department of Forensic Science,

More information

Periodic Comparison Method for Defects Inspection of TFT-LCD Panel

Periodic Comparison Method for Defects Inspection of TFT-LCD Panel Proceedings of the 7th WSEAS International Conference on Robotics, Control & Manufacturing Technology, Hangzhou, China, April 15-17, 2007 279 Periodic Comparison Method for Defects Inspection of TFT-LCD

More information

Influence of Spindle Speed on Yarn Quality of Flax/Cotton Blend

Influence of Spindle Speed on Yarn Quality of Flax/Cotton Blend The Open Textile Journal, 2011 4, 7-12 7 Influence of Spindle Speed on Yarn Quality of Flax/Cotton Blend Lawal A.S. *,1, Nkeonye P.O. 1 and Anandjiwala R.D. 2 Open Access 1 Department of Textile Science

More information

u AFIS PRO 2 The fiber process control system

u AFIS PRO 2 The fiber process control system u AFIS PRO 2 The fiber process control system Route to best practices in yarn manufacturing Information is virtually useless if not exploited to maximum advantage. That is why the USTER AFIS PRO 2 shows

More information

IMAGE PROCESSING PAPER PRESENTATION ON IMAGE PROCESSING

IMAGE PROCESSING PAPER PRESENTATION ON IMAGE PROCESSING IMAGE PROCESSING PAPER PRESENTATION ON IMAGE PROCESSING PRESENTED BY S PRADEEP K SUNIL KUMAR III BTECH-II SEM, III BTECH-II SEM, C.S.E. C.S.E. pradeep585singana@gmail.com sunilkumar5b9@gmail.com CONTACT:

More information

Textile Technology :: "Spinning" By M.H.Rana

Textile Technology :: Spinning By M.H.Rana Textile Technology :: "Spinning" By M.H.Rana HOMEPAGE Recommended Textile spinning Articles COTTON MIXING BLOWROOM PROCESS CARDING PROCESS THEORY OF CARDING CARD CLOTHING Open End Spinning RING FRAME RINGS

More information

Image processing and analysis algorithms for yarn hairiness determination

Image processing and analysis algorithms for yarn hairiness determination Machine Vision and Applications (2012) 23:527 540 DOI 10.1007/s00138-012-0411-y ORIGINAL PAPER Image processing and analysis algorithms for yarn hairiness determination Anna Fabijańska Lidia Jackowska-Strumiłło

More information