Kapade, S. D. and Khairnar, S. M. and Chaudhari, B. S. (2014) Graph Partitioning Based Normalized Cut Methods. British Journal of Mathematics & Computer Science, 5 (3). pp. 333-340. ISSN 22310851
![[thumbnail of Kapade532014BJMCS13592.pdf]](http://asian.openbookpublished.com/style/images/fileicons/text.png)
Kapade532014BJMCS13592.pdf - Published Version
Download (557kB)
Abstract
The process of image segmentation is one of the most important steps in computer vision for image retrieval, visual summary, image based modeling and in many other processes. The goal of segmentation is typically to locate certain objects of interest. In this paper, we have studied and investigated graph based normalized cut segmentation methods and proposed a technique for adding flexibility to the parameters for performance improvement. These methods are examined analytically and tested their performance for the standard images. The results obtained for the important metrics show that these methods perform better than others approaches and are computationally efficient, and useful for precise image segmentation.
Item Type: | Article |
---|---|
Subjects: | Open STM Article > Mathematical Science |
Depositing User: | Unnamed user with email support@openstmarticle.com |
Date Deposited: | 05 Jul 2023 04:25 |
Last Modified: | 18 Jun 2024 07:25 |
URI: | http://asian.openbookpublished.com/id/eprint/1037 |