Work

Rough Clustering Based Unsupervised Image Change Detection

Year: 2014
Type: preprint
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.
Language: English
Open Access status: green
OpenAlex ID: W1652219364
Cites: 13
Cited by: 4
Related to: 10