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The Design of a Single-Bit CMOS Image Sensor for Iris Recognition Applications

Department of Semiconductor Science, Dongguk University-Seoul, Seoul 04620, Korea
Author to whom correspondence should be addressed.
Sensors 2018, 18(2), 669;
Received: 10 January 2018 / Revised: 22 February 2018 / Accepted: 23 February 2018 / Published: 24 February 2018
(This article belongs to the Special Issue Image Sensors)
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This paper presents a single-bit CMOS image sensor (CIS) that uses a data processing technique with an edge detection block for simple iris segmentation. In order to recognize the iris image, the image sensor conventionally captures high-resolution image data in digital code, extracts the iris data, and then compares it with a reference image through a recognition algorithm. However, in this case, the frame rate decreases by the time required for digital signal conversion of multi-bit digital data through the analog-to-digital converter (ADC) in the CIS. In order to reduce the overall processing time as well as the power consumption, we propose a data processing technique with an exclusive OR (XOR) logic gate to obtain single-bit and edge detection image data instead of multi-bit image data through the ADC. In addition, we propose a logarithmic counter to efficiently measure single-bit image data that can be applied to the iris recognition algorithm. The effective area of the proposed single-bit image sensor (174 × 144 pixel) is 2.84 mm2 with a 0.18 μm 1-poly 4-metal CMOS image sensor process. The power consumption of the proposed single-bit CIS is 2.8 mW with a 3.3 V of supply voltage and 520 frame/s of the maximum frame rates. The error rate of the ADC is 0.24 least significant bit (LSB) on an 8-bit ADC basis at a 50 MHz sampling frequency. View Full-Text
Keywords: Analog-to-digital converter; CMOS image sensor; edge detection; iris recognition; XOR Analog-to-digital converter; CMOS image sensor; edge detection; iris recognition; XOR

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Park, K.; Song, M.; Kim, S.Y. The Design of a Single-Bit CMOS Image Sensor for Iris Recognition Applications. Sensors 2018, 18, 669.

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