Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

Color Image Segmentation Using Improved Method of Normal Cut

Authors
Adnan Ahmad, Guo Ling, Hassan Hayat
Corresponding Author
Adnan Ahmad
Available Online June 2017.
DOI
https://doi.org/10.2991/caai-17.2017.130How to use a DOI?
Keywords
grouping; image segmentation; graph partitioning; normalized cuts (ncut); graph theory
Abstract
Image segmentation is a key problem in several fields of science and technology, for E.g. medicine, robotics, and industrial development. The importance of perceptual grouping and organization in vision possess numerous significant factors, such as similarity, proximity, and good continuation, which lead towards the visual grouping in present. However, even to this day, many of the computational issues of perceptual grouping have remained unresolved. This article presents image segmentation as a graph partitioning problem and proposed modified method of normalized cuts, for segmenting the graph. The normalized cut criterion measures both the total dissimilarity between the different groups as well as the total similarity within the groups. The proposed algorithm deals with the color images which give more clear understanding of an image as compared to the black and white images. The experimental results show that the proposed algorithm gives better, clear and more visible understanding of UAV images.
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Proceedings
2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-360-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/caai-17.2017.130How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Adnan Ahmad
AU  - Guo Ling
AU  - Hassan Hayat
PY  - 2017/06
DA  - 2017/06
TI  - Color Image Segmentation Using Improved Method of Normal Cut
BT  - 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 585
EP  - 588
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.130
DO  - https://doi.org/10.2991/caai-17.2017.130
ID  - Ahmad2017/06
ER  -