An Alternative Graph Cut Algorithm for Morphological Edge Detection

Abstract

Problem statement: Image analysis has some basic importance of edge detection. Characterize the object boundaries are helpful for object segmentation, registration and identification in a scene. There are many methods for edge detection, but it can be identified by two major methods, search-based and zero-crossing based. Approach: Proposed method tries to follow searching the edge points by applying graph cuts in the place of morphological approach. The graph cut edge detection algorithm is very effective to detect edges with minimum searches. Results: The new approach produces connectives edge boundary with recursive approach in short duration comparatively with morphological approach. It is obtained by identifying the edge points with cut measure within its boundary. Conclusion: The graph cut algorithm detect boundary for any shapes with normal structure, this identification of edges in a complex background is always required a lot of user inputs. In each level only the local neighboring boundaries to be separated with labels. It is optimized approach for unknown region boundaries in complex basins.