Implementation and performance analysis of Video Edge Detection system on Multiprocessor Platform

This paper presents an agile development, implementation of Edge Detection on SMT8039 based Video And Imaging module. With the development of video processing techniques its algorithm becomes more complicated. High resolution and real time application cannot be implemented with single CPU or DSP. The system offers significant performance increase over current programmable DSP-based implementations. This paper shows that the considerable performance improvement using the FPGA solution results from the availability of high I/O resources and pipelined architecture. FPGA technology provides an alternative way to obtain high performance. Prototyping a design with FPGA offer some advantages such as relatively low cost, reduce time to market, flexibility. Another capability of FPGA is the amount of support of logic to implement complete systems/subsystems and provide reconfigurable logic for purpose of application specific based programming. DSP's to provide more and more power and design nearly any function in a large enough FPGA, this is not usually the easiest, cheapest approach. This paper designed and implemented an Edge detection method based on coordinated DSP-FPGA techniques. The whole processing task divided between DSP and FPGA. DSP is dedicated for data I/O functions. FPGA's task is to take input video from DSP to implement logic and after processing it gives back to DSP. The PSNR values of the all the edge detection techniques are compared. When the system is validated, it is observed that Laplacian of Gaussian method appears to be the most sensitive even in low levels of noise, while the Robert, Canny and Prewitt methods appear to be barely perturbed. However, Sobel performs best with median filter in the presence of Gaussian, Salt and Pepper, Speckle noise in video signal.