Local threshold and boolean function based edge detection

Localization of edge points in images is one of the most important starting steps in image processing. Many varied edge detection techniques have been proposed Different edge detectors present distinct and different responses to the same image, showing different details. This work will present a new approach for edge detection. The actual gray level image is locally thresh olded using local mean value to make a binary image. The binary image is ch ecked for edges by comparing with the known edge like patterns, utilizing t he Boolean algebra. This approach recognizes nearly all-actual edges and ed ges clue to noise. For removing edges due to noise, we adopt another approa ch. This time the actual image is globally thresholded by variance value of the image. The two resulting images are logically ANDed to get the final e dge map.