A power-efficient CMOS image sensor with current-mode 1-bit log-gradient feature extractor for always-on object detection

Abstract

This paper presents a power-efficient CMOS image sensor (CIS) for always-on object detection by using 1-bit log-gradient feature extraction in analog current domain. Compared with traditional image sensors with high-resolution ADCs, the proposed CIS extracts gradients in ratio form and generates feature maps at 1-bit resolution, which eliminates unnecessary background information and illumination-related data, and reduces the data computation in the later detector. The system containing the proposed CIS and back-end ANN detector is modeled with python and the simulation achieves an accuracy of 93.2 % for person detection. The CIS employs current mode divider and comparator to compute the gradient ratios. An accurate and configurable muti-input and muti-output (MIMO) current divider is proposed, composed of two cascaded modified second generation current controlled conveyors (M-CCCIIs). The proposed CIS was fabricated in a 0.18 μm standard CMOS process and realized a frame rate of 170 fps and an energy efficiency of 337 pJ/pixel in a power consumption of 1.1 mW. Experimental results show that the proposed CIS can realize the function of extracting log-gradients.