Content Based Image Retrieval Using GLCM & CCM

B Santosh Kumar¹

¹Assistant Professors, Department of ECE, CJITS, Jangaon, Warangal, AP, India

Abstract

The growth of digital image archives is increasing the need for the tools that effectively filter and efficiently search through large amounts of visual data. Towards this goal we propose a technique by which the color content and texture features of images is automatically extracted by using content based image retrieval (CBIR). CBIR has become one of the most active research areas in the past few years. Many visual feature representations have been explored. Image CBIR is emerging as an important research area with application to digital libraries, data mining, education, medical imaging, crime prevention and multimedia databases. The focus is on image processing aspects and in particular using color and texture features. Color feature is extracted by HSV. The color feature is represented by color histogram and texture feature extraction is obtained by using gray-level co-occurrence matrix (GLCM) or color co-occurrence matrix (CCM). Through the quantification of HSV color space, we combine color features and GLCM as well as CCM separately.

Keywords

• Digital Image, color, CBIR, GLCM & CCM

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Cite this Article as Follows

B Santosh Kumar. Content Based Image Retrieval Using GLCM & CCM. International Conference on Information Engineering, Management and Security 2014. Vol. 1. Chennai: Association of Scientists, Developers and Faculties, 2014. 67-74. Print.