SEGMENTING DIGITAL IMAGES USING EDGE DETECTION
Amit Chaudhary, Tarun Gulati · 2013
Image segmentation is an active topic of research for last many years. Edge detection in images significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. In this paper, the two most commonly used edge detection methods (Laplacian and Sobel edge detectors) are discussed. It is found that Sobel edge detection algorithms perform better than Laplacian algorithms; however, the false edges are high in both cases for blurred or low resolution images. Therefore, a new algorithm and set of filters (kernels) is proposed and its results are compared with the Sobel and Laplacian filters for three images. From the results obtained it is found that the proposed algorithm performs better than in terms of less false edges than the Sobel and Laplacian filters.