Study of Image Segmentation Schemes and Their Applications to Microscopic Images

Abstract

Image Segmentation is one of the most important concerns in digital image processing. It's a long standing problem in computer vision. Often it is viewed as an ill-defined problem in comparison to other vision tasks which have apparently well defined objectives, such as detection, recognition, and tracking. It is fair to say that computer vision or image understanding is all about parsing images. Different fundamental algorithms of image segmentation are implemented like Hough Transform Algorithm (Edge Linking & Boundary Detection), Region Growing (Similarity Based Segmentation), Iterative Thresholding Method. A new approach of Image Segmentation based on Maximum A posteriori is implemented which uses the concept of Baye's Theorem. A segmentation based problem to count number of white and black nano particles approximately in a microscopic image of a ceramic material is successfully
solved.