An Efficient Hardware Implementation of Canny Edge Detection Algorithm

Edge detection is an essential technique used in many image processing applications. Among the various edge detection techniques available, the canny edge detection algorithm has been widely recognized for its superior performance. However, its implementation in real time systems can be computationally complex and expensive in terms of hardware costs, leading to increased latency. To address these challenges, a novel approach to canny edge detection has been proposed. This algorithm utilizes approximation methods to replace complex operations, thereby reducing computational complexity. In addition, pipelining techniques are employed to further decrease latency. The proposed canny edge detection algorithm has been implemented on Xilinx Virtex 5 FPGA, a field programmable gate array. Compared to previous hardware architectures for canny edge detection, the new architecture requires fewer hardware resources, resulting in reduced costs. Furthermore, the algorithm is able to detect the edges of a 512 x 512 image in just 1ms. In conclusion, the proposed canny edge detection algorithm offers an efficient and cost effective solution for real time image processing applications. By utilizing approximation methods and pipelining techniques, it achieves superior performance while minimizing hardware costs and latency. Keerthana P | Mr. K. Raja "An Efficient Hardware Implementation of Canny Edge Detection Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-5 , October 2023, URL: https://www.ijtsrd.com/papers/ijtsrd59863.pdf Paper Url: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/59863/an-efficient-hardware-implementation-of-canny-edge-detection-algorithm/keerthana-p