Publication Type : Book Chapter
Publisher : Springer Berlin Heidelberg
Source : Proceedings of ICMET 2011 (London, UK), Advances in Intelligent and Soft Computing, Springer Berlin Heidelberg, Vol. 125, pp. 767-772, 2011.
Url : https://link.springer.com/chapter/10.1007/978-3-642-27329-2_105
Campus : Kochi
School : School of Computing
Department : Computer Science
Year : 2012
Abstract : This paper proposes a content based image retrieval system using the local colour and texture features of image sub blocks. The colour features are extracted from the histograms of the three channels of RGB colour space. Gray Level co- occurrence matrix (GLCM) is used for extracting the texture features. A combined colour and texture feature vector is computed for each sub block and Euclidean distance measure is used for computing the distance between the features of the query image and candidate images in the database. Preliminary experimental results shows that the proposed method provides better retrieving results than some of the existing methods based on colour and texture.
Cite this Research Publication : E R Vimina, K Poulose Jacob, "Image Retrieval using Local Colour and Texture Features", Proceedings of ICMET 2011 (London, UK), Advances in Intelligent and Soft Computing, Springer Berlin Heidelberg, Vol. 125, pp. 767-772, 2011.