To: Author

Article Fingerprint
ReserarchID
CST77LV4
Choose where you want to hide AI Takeaway. Your site-wide choice will be remembered in this browser.
Texton is a extensively applied approach for texture analysis. This technique shows a strong dependence on certain number of parameters. Unfortunately, each variation of values of any parameter may affect the texture characterization performance. Moreover, micro structure texton is unable to extract texture features which also have a negative effect on the classification task. This paper, deals with a new descriptor which avoids the drawbacks mentioned above. To address the above, the present paper derives a new descriptor called Fuzzy Based Texton Binary Shape Matrix (FTBSM) for clear variation of any feature/parameter. The proposed FTBSM are defined based on similarity of neighboring edges on a 3×3 neighborhood. With micro-structures serving as a bridge for extracting shape features and it effectively integrates color, texture and shape component information as a whole for texture classification. The proposed FTBSM algorithm exhibits low dimensionality. The proposed FTBSM method is tested on Vistex and Akarmarble texture datasets of natural images. The results demonstrate that it is much more efficient and effective than representative feature descriptors, such as logical operators and GLCM and LBP, for texture classification.
Dr. P.Chandra Sekhar Reddy, B.Eswara Reddy. 2013. "Fuzzy Based Texton Binary Shape Matrix (FTBSM) for Texture Classification". Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 12 (GJCST Volume 12 Issue F15).
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
v1.2
Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.
Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.
Total Score: 147
Country: India
Subject: Global Journal of Computer Science and Technology
Authors: Dr. P.Chandra Sekhar Reddy, B.Eswara Reddy (PhD/Dr. count: 1)
View Count (all-time): 444
Total Views (Real + Logic): 2619
Total Downloads (simulated): 230
Publish Date: 2012 03, Thu
Monthly Totals (Real + Logic):
We use cookies and similar technologies to improve site performance, understand traffic, and enhance your publishing experience. Cookie Policy
Choose which optional cookies Global Journals can use. Your preference applies across this platform and can be updated any time.
These cookies are required for core website functionality and security.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.