Paper Contents
Abstract
Image segmentation is a fundamental process in computer vision that involves dividing an image into different segments or regions based on their similarity. The purpose of image segmentation is to extract meaningful information from an image and make it easier to analyze and interpret. There are various image segmentation techniques, including thresholding, edge-based segmentation, region-based segmentation, and clustering-based segmentation. Each technique has its advantages and disadvantages, and the choice of the appropriate technique depends on the application's requirements. Image segmentation has numerous applications in various fields, including medical imaging, computer vision, and robotics. The success of these applications depends on the accuracy and efficiency of the image segmentation process. This research paper provides an overview of the different techniques used in image segmentation and their applications
Copyright
Copyright © 2023 Sarthak Bisht. This is an open access article distributed under the Creative Commons Attribution License.
