Low-power edge detection based on ferroelectric field-effect transistor
Jiajia Chen, Jiacheng Xu, Jiani Gu, Bowen Chen, Hongrui Zhang, Haoji Qian, Huan Liu, Rongzong Shen, Gaobo Lin, Xiao Yu, Miaomiao Zhang, Yian Ding, Yan Liu, Jianshi Tang, Huaqiang Wu, Chengji Jin, Genquan Han
Abstract
Edge detection is one of the most essential research hotspots in computer vision and has a wide variety of applications, such as image segmentation, target detection, and other high-level image processing technologies. However, efficient edge detection is difficult in a resource-constrained environment, especially edge-computing hardware. Here, we report a low-power edge detection hardware system based on HfO2-based ferroelectric field-effect transistor, which is one of the most potential non-volatile memories for energy-efficient computing. Different from the conventional edge detectors requiring sophisticated hardware for the complex operation such as convolution and gradient, the proposed edge detector is analogue-to-digital converter free and loaded into a multi-bit content addressable memory, which only needs one 4 × 4 ferroelectric field-effect transistor NAND array. The experimental results show that the proposed hardware system is able to achieve efficient image edge detection at low power consumption (~10 fJ/per operation), realizing no-accuracy-loss, low-power and analogue-to-digital-converter-free hardware system, providing a feasible solution for edge computing. The proposed edge detection based on ferroelectric field effect transistor does not rely on conventional convolution operation, realizing no-accuracy-loss, low-power (~10 fJ/per operation) and analogue-to-digital converter (ADC)-free edge computing.