Unsupervised Segmentation of Remote Sensing Images using FD Based Texture Analysis Model and ISODATA

S. Hemalatha and S. Margret Anouncia
Additional contact information
S. Hemalatha: School of Information Technology, VIT University, Vellore, India
S. Margret Anouncia: School of Computer Science and Engineering, VIT University, Vellore, India

International Journal of Ambient Computing and Intelligence (IJACI), 2017, vol. 8, issue 3, 58-75

Abstract: In this paper, an unsupervised segmentation methodology is proposed for remotely sensed images by using Fractional Differential (FD) based texture analysis model and Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA). Essentially, image segmentation is used to assign unique class labels to different regions of an image. In this work, it is transformed into texture segmentation by signifying each class label as a unique texture class. The FD based texture analysis model is suggested for texture feature extraction from images and ISODATA is used for segmentation. The proposed methodology was first implemented on artificial target images and then on remote sensing images from Google Earth. The results of the proposed methodology are compared with those of the other texture analysis methods such as LBP (Local Binary Pattern) and NBP (Neighbors based Binary Pattern) by visual inspection as well as using classification measures derived from confusion matrix. It is justified that the proposed methodology outperforms LBP and NBP methods.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJACI.2017070104 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jaci00:v:8:y:2017:i:3:p:58-75

Access Statistics for this article

International Journal of Ambient Computing and Intelligence (IJACI) is currently edited by Nilanjan Dey

More articles in International Journal of Ambient Computing and Intelligence (IJACI) from IGI Global
Bibliographic data for series maintained by Journal Editor ().