AUTOREGRESSIVE MODEL BASED ON BAYESIAN APPROACH FOR TEXTURE REPRESENTATION

Autor:	T. Karthikeyan, R. Krishnamoorthy
Jazyk:	angličtina
Rok vydání:	2012
Předmět:	Texnum Texspectnum Microtexture K-Means Algorithm Supervised Classification Unsupervised Classification Telecommunication TK5101-6720 Computer applications to medicine. Medical informatics R858-859.7
Zdroj:	ICTACT Journal on Image and Video Processing, Vol 3, Iss 1, Pp 485-491 (2012)
Druh dokumentu:	article
ISSN:	0976-9099 0976-9102
Popis:	In this study autoregressive model based on Bayesian approach is proposed for texture classification. Based on auto correlation coefficients, micro textures are identified and represented locally and then globally. The identified micro texture is represented as a local description, called texnum. The global descripter, texspectnum, is obtained by simply observing the numbers of occurrences of the texnums that cover the entire image. The proposed representation scheme has been employed in both supervised and unsupervised classifications of textured images. The supervised classification is based on simple tests of hypotheses and the unsupervised classification is based on the modified K-means algorithm with minimum distance classifiers. The proposed method is demonstrated for classification of different types natural textured images. The average correct classification is better than the existing methods.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/52e1d4730b11482f845e6f9abb80deb8 Zobrazit plný text záznamu View record in DOAJ