An Improved Algorithm for Segmentation of Grey and Color Images
MA Long-sheng · Acta Simulata Systematica Sinica · 2001
Edge detection is one of the most important techniques in image processing; it is often used in the field of image analysis and image recognition for many applications. However edge detection alone is not a whole image segmentation process, because usually the detected edges are not continuous and many loose edge points exist in high detail areas. To improve the accuracy of boundary locations and region homogeneity as well as to reduce the error rate in image segmentation, we present a novel approach called edge growing to attack edge discontinuity after edge point detection, therefore high detail areas enclosed by the adjacent salient regions can be indirectly extracted as a large areas. The algorithms can be embedded in other complicated segmentation procedures to incorporate edge information.