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Implementation of Improved Sobel Edge Detection Algorithm Using Xilinx System Generator
Abstract
Edge detection plays a vital role in image analysis. Up to now several edge detection methods have been developed such as Roberts, Prewitt, Sobel, Zero-crossing, Canny, etc. In this paper, a new improved sobel edge detection operator is proposed because the basic sobel algorithm is failed to identify the edges in noisy situation. The structure of our proposed edge detector makes the process robust against noise. In this paper the sobel algorithm is improved by using ANT colony optimization techniques and implemented for better performance. Firstly, the output of initial stage edge detection methods analyzed with basic sobel edge detection and performance improvement is identified on different application scenario. Field Programmable Gate Array (FPGA) technology becomes an alternative for the implementation of software algorithms. The proposed system for edge detection is implemented with the combination of XSG (Xilinx System Generator) and Matlab environments.
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References
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