Abstract
Detection of edge is a terminology in image processing and computer vision particularly in the areas of feature detection and extraction to refer to the algorithms which aims at identifying points in a digital image at which the image brightness changes sharply or more formally has discontinuities. Edge is a basic feature of image. The image edges include rich information that is very significant for obtaining the image characteristics by object recognition. Edge detection refers to the process of identifying and locating sharp discontinuities in an image. So, edge detection is a vital step in image analysis and it is the key of solving many complex problems. This paper, describes edge detection algorithms for image segmentation using various computing approaches which have got great fruits. Experimental results prove that Canny operator is better than Prewitt and Sobel for the selected image. Subjective and Objective methods are used to evaluate the different edge operators. The performance of Canny, Sobel and Prewitt Edge Detection are evaluated for detection of edges in digital images.
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