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We designed and fabricated a vision chip for edge detection with a 160×120 pixel array by using 0.35 ㎛ standard complementary metal-oxide-semiconductor (CMOS) technology. The designed vision chip is based on a retinal structure with a resistive network to improve the speed of operation. To improve the quality of final edge images, we applied a saturating resistive circuit to the resistive network. The light-adaptation mechanism of the edge detection circuit was quantitatively analyzed using a simple model of the saturating resistive element. To verify improvement, we compared the simulation results of the proposed circuit to the results of previous circuits.

In this paper, a vision chip for edge detection based on the structure of a biological retina is introduced. The chip processes an image in a bio-inspired vision mechanism; therefore, it is proper for the neuromorphic systems. Logarithmic active pixel sensor (APS) was applied to the vision chip. By applying a MOS-type photodetector to the logarithmic APS, we could achieve sufficient output swing for the vision chip in natural illumination condition. A correlated-double sampling technique was applied to the chip for noise suppression. In addition, a CMOS buffer circuit is commonly used for both raw and smoothed images by using additional switches. This structure helps reduce the total number of MOSFETs for a unit-pixel and noise. A vision chip with a 160×120 pixel array was fabricated using a 0.35 μm double-poly four-metal CMOS technology, and its operation was successfully demonstrated.

CMOS vision chips for edge detection based on a resistive circuit have recently been developed. These chips help develop neuromorphic systems with a compact size, high speed of operation, and low power dissipation. The output of the vision chip depends dominantly upon the electrical characteristics of the resistive network which consists of a resistive circuit. In this paper, the body effect of the MOSFET for current distribution in a resistive circuit is discussed with a simple model. In order to evaluate the model, two 160×120 CMOS vision chips have been fabricated by using a standard CMOS technology. The experimental results have been nicely matched with our prediction.

In this paper, a vision chip for a contrast-enhanced image based on a structure of a biological retina is introduced. The key advantage of this structure is high speed of signal processing. In a conventional active pixel sensor (APS), the charge accumulation time limits its operation speed. In order to enhance the speed, a logarithmic APS was applied to the vision chip. By applying a MOS-type photodetector to the logarithmic APS, we could achieve sufficient output swing for the vision chip in natural illumination condition. In addition, a CMOS buffer circuit, a common drain amplifier, is commonly used for both raw and smoothed images by using additional switches. By using the switch-selective resistive network, the total number of MOSFETs for a unit pixel and the fixed-pattern noise were reduced. A vision chip with a 160×120 pixel array was fabricated using a 0.35 mm double-poly four-metal CMOS technology, and its operation was experimentally investigated.

In this paper, a vision chip for edge detection based on the structure of a biological retina is introduced. The key advantage of the structure is high speed of operation. However, the charge accumulation time of a conventional active pixel sensor limits its operation speed. In order to enhance the operation speed, a logarithmic APS using a metal-oxide-semiconductor-type photodetector was applied into the vision chip. By applying a MOS-type photodetector to a logarithmic APS, we could achieve sufficient output swing for a bio-inspired vision chip. We fabricated a 160times120 bio-inspired complementary metal-oxide-semiconductor vision chip using 0.35 mum two-poly four-metal complementary metal-oxide-semiconductor technology, and then investigated.