Open AccessAssessment of Object Segmentation Techniques for Object Based Image Retrieval
Author(s) -
Hema Laxmidevinoolvi,
M. V. Sudhamani
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b1048.1292s19
Subject(s) - artificial intelligence , segmentation based object categorization , thresholding , computer vision , image segmentation , computer science , scale space segmentation , segmentation , image texture , object (grammar) , pattern recognition (psychology) , region growing , image processing , image (mathematics)
Objects relates more to human perception than any other attributes of an image. Image segmentation is a significant image processing technique to get the objects from complex image background. This work assesses the techniques of segmentation from basic global thresholding, edge based methods up to the advanced techniques such as K-means, Active Contour Model (Snakes) segmentation approaches. Later, results are post processed with the help of morphological operations and make them suitable for object based image retrieval. It also provides the comparative analysis and empirical assessment of performance of the proposed modified segmentation approaches.