Rough Clustering Based Unsupervised Image Change Detection
Computer Vision and Pattern Recognition
2014-04-25 v1 Artificial Intelligence
Abstract
This paper introduces an unsupervised technique to detect the changed region of multitemporal images on a same reference plane with the help of rough clustering. The proposed technique is a soft-computing approach, based on the concept of rough set with rough clustering and Pawlak's accuracy. It is less noisy and avoids pre-deterministic knowledge about the distribution of the changed and unchanged regions. To show the effectiveness, the proposed technique is compared with some other approaches.
Cite
@article{arxiv.1404.6071,
title = {Rough Clustering Based Unsupervised Image Change Detection},
author = {Chandranath Adak},
journal= {arXiv preprint arXiv:1404.6071},
year = {2014}
}
Comments
Proc. IEEE Conf. #30853, International Conference on Human Computer Interactions (ICHCI'13), Chennai, India, 23-24 Aug., 2013. (In Press)