Review on Region-Based Segmentation Using Watershed and Region Growing Techniques and their Applications in Different Fields

Abstract

In digital image processing and computer vision, segmentation operation for an image refers to dividing an image into multiple image segments, and the significant purpose of segmentation operation is to depict an image in a way so that the analysis process of the objects of interest is easier and more accurate. The region-based segmentation scheme act for finding similarities between adjacent pixels to detect each region that constructs the image. Similarity scales have based on different features, in a grayscale image, the scale may be referred to as textures and other spatial appearances, and also the variance in intensity of a region and so on. Significantly, many applications in different fields involved region-based segmentation for instance remote sensing, medical application, and others for recognizing interesting objects in an image. In this paper, two techniques for segmentation operation in region-based which are region growing and watershed are reviewed.

Texture and pixel intensity characterization-based image segmentation with morphology and watershed techniques

“…In the operation of image segmentation, two major classifications are regarded that defined as layer-based and block-based segmentation in an image. The approaches in the second classification are categorized based on two characteristics: discontinuity and similarity, and are divided into three groups: region-based strategies, edge-based or boundary-based procedures, and hybrid approaches [2]. Image segmentation is commonly used to define objects and edges in an image.…”