Watershed Transform on Image Segmentation and Data Classification

ABSTRACT Watershed transform is usually adopted for image segmentation in the area image processing and image analysis The concept of watershed transform is based on a processing simulating the immersion of a landscape in a lake that is dams have to be built to prevent the merging of different catchment basins. In this paper firstly the algorithm of watershed transform are firstly introduced. Two novels methods utilizing watershed transform are proposed. first we propose an effective noise removal method to resolve the problem of small object detection with low contrast and second we propose a methods call "watershed classifier" for data clustering and classification using the watershed transform. Most watershed algorithm are utilized for image data where as the proposed watershed classifier is capable of classifying arbitrary data without prior knowledge