Article DOI: 10.21307/ijssis-2018-013 Issue 0 Vol. 0 Implementation of 144 64 Pixel Array Bezel-Less Cmos Fingerprint Sensor Seungmin Jung School of Information and Technology, Hanshin University, 137 Hanshindae-gil, Osan-si, Korea. E-mail: jasmin@hs.ac.kr. This article was edited by SMN Arosha Senanayake. Received for publication April 26, 2018. Abstract This paper proposes CMOS integrated 144 64 pixel array fingerprint sensor without a bezel electrode. In this paper, the architecture of CMOS capacitive fingerprint sensor readout circuit is presented for general type of a switched capacitive integrator scheme. The pipelined scan driver is included in the fingerprint sensor for fast image capture. It is implemented on 0.35 μ m standard CMOS process technology. The operation is validated by SPECTRE for one-pixel and RTL simulation including logic synthesis for a full chip design on condition of 0.35 µm typical CMOS process and 3.3 V power. The layout is performed by full custom flow for sensor cell array and auto P&R for a full chip. The area of a full chip is 4943 μ m 3943 μm and the gate count is 542,000. The area of one-pixel is 48 48 µm 2. The pitch is 50 µm and image resolution is 508 dpi and power consumption is less than 3 ma. Keywords Bezel-less, capacitive fingerprint, fingerprint sensor, readout circuit, switched capacitive integrator. The solid-state capacitive fingerprint sensors are adopted on mobile application environment like a mobile phone. As far as technology trends are concerned, CMOS semiconductor, ultrasonic, and optical methods have been applied to manufacturing processes of fingerprint recognition sensors. The capacitive fingerprint sensor by semiconductor standard CMOS process is the most excellent in the cost, authentication accuracy, and reliability. Most of them rely on capacitive coupling between the finger and matrix of small metal plates to detect ridges and valleys on the finger surface. Each plate forms a pixel of the resulting image and requires circuitry to measure the capacitance. One of the most important performances of a capacitive sensor is the sensitivity capability since the detected capacitance is very small of the order of femto-farads. There are bezel and bezel-less sensors in the capacitive fingerprint sensors. However, fingerprint sensors applied to mobile phones recently are mostly bezel type in terms of technology and design. The image of the bezel fingerprint sensor is excellent because the terminals for directly injecting charges are in contact with the skin. At coating thickness over 200 µm thick, it is very difficult for capacitive fingerprint sensors to obtain fingerprint image because the greater the coating thickness between the sensor and the fingerprint, the lower the signal strength. As the molding thickness increases, the parasitic signal becomes rather bigger than the main signal, and various circuit techniques for solving the problem are proposed. This paper proposes parasitic insensitive fingerprint sensor with the switched capacitor integrator (Jung et al., 2005; Liu et al., 2012; Jung, 2013; Yeo, 2013a, 2013b, 2014, 2015; Gao et al., 2014; Jung, 2014) and implements the area type 144 64 array fingerprint sensor LSI with pipelined architecture for high-speed image capture. The proper operation is validated by HSPICE for one pixel and RTL simulation including logic synthesis for a full chip design on condition of 0.35 µm typical CMOS process and 3.3 V 2018 Authors. This work is licensed under the Creative Commons Attribution- NonCommercial-NoDerivs 4.0 License https://creativecommons.org/licenses/bync-nd/4.0/ 1
Implementation of 144 64 pixel array bezel-less cmos fingerprint sensor power. The layout is performed by full custom flow for one pixel and auto P&R for a full chip. Fingerprint detection circuit and chip architecture The pixel-level detection circuit of capacitive sensing has been introduced as shown in Figure 1 (Jung, 2016). The circuit can use the capacitive sensing range of full supply voltage, because it combines a passive and parasitic-insensitive integrator. The circuit is suitable for low voltage and low power applications. The sensor plate is shielded by a metal to prevent the noise from the circuit under the sensor plate, which forms a parasitic capacitance between the sensor plate and the metal shield. Cp1 must be removed, because it is very large compared to Cf. To remove this parasitic capacitance, the output is applied to the bottom node of Cp1 to maintain the same potential between the both nodes of Cp1, which maximizes the sensitivity of the fingerprint sensor. Figures 2 and 3 show the functional block diagram and floor planning of 144 64 fingerprint sensor chip. General biometric sensors use analog-to-digital converter (ADC) and programmable gain amplifier (PGA) to get good image quality. The detected signal of a sensor pixel is amplified to get reasonable signal level Figure 1: Pixel-level sensor scheme and output voltage. 2
Figure 2: Functional block diagram of fingerprint sensor chip. Figure 3: Pipelined scan fingerprint sensor driver architecture. 3
Implementation of 144 64 pixel array bezel-less cmos fingerprint sensor Figure 4: Floorplan of fingerprint sensor chip. for ADC, which might increase system complexity. This paper proposes a fingerprint sensor amplify the detected signal by integration times using variable clock generator shown in Figure 2 rather than an amplifier. The 144 64 pixel array fingerprint sensor is implemented with 0.35 μ m standard CMOS process. The proposed circuit is designed to adjust the charge integration time from 1 to 7 times of 16 clocks with a control of 3 bit signal period, so it takes up to 112 clock times per pixel. When integrating for 112 clocks at 10 MHz main clock, the designed fingerprint sensor chip takes about 922 ms to obtain a frame fingerprint image of 144 64 pixel array. Generally, the fingerprint sensor chip should take about 0.5 s or less to capture and authenticate the image. In this paper, the pipelined scan fingerprint sensor driver architecture was applied, which helps to reduce the fingerprint image capture time and power consumption effectively. Variable clock generator block generates vclk_out, hold_out_p, and hold_nor signal. These signals are used to control pipelined scan fingerprint sensor driver architecture. The 144 64 sensor cell arary with pipelined scan architecture was applied to the fingerprint sensor. The fingerprint sensor is consisted of 144 64 sensor cells array with YDEC and XMUX and 16 bits shift ring-counter. The 16 bits shift ring-counter generates a pipelined scan signal which controls parallel scanner to drive maximum eight sensor cells simultaneously. 2-stage of 16 by 18 XMUX selects a proper column output for the proper evaluation sensor cell. Two memory cells are used to capture fingerprint output image. Figure 5 shows RTL simulation result of the proposed pipelined architecture. The fingerprint sensor proposed in the pipeline structure takes about 150 ms to capture the image, resulting in excellent response speed and low power consumption. Figure 5: RTL simulation result of pipelined architecture. 4
sensor core. The layout is performed by full custom flow for one-pixel and auto P&R for the full chip. The area of the full chip is 19.5 mm 2 (4,943 μ m 3,943 μ m) and the gate count is 542,000. The area of one-pixel is 50 µm 50 µm. Pitch is 50 µm and image resolution is 508 dpi. Acknowledgements This work was supported by Hanshin University Research Grant. VLSI implementation Figure 6 shows 144 64 pixel array chip layout and the die size is 7,569 μ m 4,569 μ m on 0.35 μ m standard CMOS process. The circuit includes two compiled SRAM memorys, IO slot and analog block with ADC, PGA. The layout area of one pixel is 48 μ m 48 μm and pixel pitch is 50 μ m. The gate count is 653,491. The layout of 144 64 array core cell is performed by full custom design method and the full chip is performed by auto placement and routing of cell-based design method. Conclusions Figure 6: 144 64 pixel array chip layout (7,569 μ m 4,569 μ m @0.35 μ m CMOS process). This paper implements 80 64 array high sensitive fingerprint sensor with the parasitic insensitive charge transfer integrator. The fingerprint sensor cell uses an active output voltage feedback integrator. The detection circuit of one pixel includes a pixel level charge transfer and parasitic insensitive integrator with a differential amplifier with pmos input. A multiple integration scheme is proposed to improve signal-to-noise ratio and amplify the sensing signal, which enables and robust fingerprint sensor driver architecture. The parasitic insensitive charge transfer circuit includes a simple differential amplifier and two switches to remove parasitic capacitance and transfer charge. The operation is validated by HSPICE for one pixel and RTL simulation including logic synthesis for the full chip design on condition of 0.18 µm typical CMOS process and 1.8 V power. The voltage difference between a ridge and valley is about 215 mv after 10 clock cycles and 367 mv after 20 clock cycles. The maximum frequency of cell operation is 10 MHz. The simulation results show the parasitic insensitive characteristics which increase touch sensitivity of the circuit. Full chip logic is synthesized and integrated with 80 64 array Literature Cited Gao, M., Hu, X., Cao, B., and Li, D. 2014. Fingerprint sensors in mobile devices, 2014 IEEE 9th Conference on Industrial Electronics and Applications (ICIEA), 1437 40. Jung, S. 2016. A modified architecture for fingerprint sensor of switched capacitive integrator scheme. International Journal of Bio-Science and Bio-Technology 8(6): 139 44. Jung, S.-M. 2013. Active capacitive-sensing circuit technique for image quality improvement on fingerprint sensor. Journal of Next Generation Information Technology(JNIT) 4(3): 47 53. Jung, S.M. 2014. An implementation of parasitic insensitive 128 100 pixels fingerprint sensor using modified switched capacitor integrator. International Journal of Bio-Science and Bio-Technology(IJBSBT) 6(6): 121 8. Jung, S.M., Nam, J.M., Yang, D.H., and Lee, M.K. 2005. A CMOS integrated capacitive fingerprint sensor with 32-bit RISC microcontroller. IEEE Journal of Solid-State Circuits 40: 1745 50. Liu, J.-C., Hsiung, Y.-S., and Lu, M. 2012. A CMOS micromachined capacitive sensor array for fingerprint detection. IEEE Journal of Solid-State Circuits 12(5): 1004 10. Yeo, H. 2013a. A parasitic-insensitive charge transfer circuit for capacitive sensing based on switched capacitor integrator. Future Information Communication Technology and Applications, Lecture Note in Electrical Engineering 235: 445 52. Yeo, H. 2013b. A parasitic-insensitive charge transfer circuit for capacitive sensing using active output voltage feedback technique. Journal of Next Generation Information Technology(JNIT) 4(5): 164 71. Yeo, H. 2015. A new fingerprint sensor based on signal integration scheme using charge transfer circuit. International Journal of Bio-Science and Bio-Technology (IJBSBT) 7(1): 29 38. Yeo, H. 2014. Analysis and performance comparison of charge transfer circuits for capacitive sensing. Journal of Next Generation Information Technology 5(1): 16 26. 5