Robust edge detection based on Modified Moore-Neighbor

Abstract

Edge detection is a fundamental step in image segmentation and one of the most important steps to recognize the features of objects. In this paper, we proposed an edge detection method using modified Moore-Neighbor algorithm. The Modified Moore-neighbor algorithm is used as boundary tracing for detection and feature extraction. Further, range filter is incorporated with modified Moore-Neighbor to detect the edges of objects. The proposed edge detection can extract the true edges as well as features of an object and is robust to noise. We have considered both objective evaluation and subjective evaluation to verify the results. The image analysis parameters are considered for subjective evaluation. Further, a total number of 24 BSD (Berkeley Segmentation Database) images are considered for subjective evaluation using the proposed method and compared with the other existing methods. The results obtained using the proposed modified Moore-Neighbor algorithm for different test images and BSD images are found to be promising. Therefore, proposed edge detection method warrants further investigation.