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Paper Title
Comparative Study on Image Retrieval using Color, Texture and Color-Texture, Based on Semantic Properties
Authors
  Ramya Nagaraju Gowda,  Vinodha H N

Abstract
CBIR is the study of browsing digital images from large database collection. This is a growing research area having many applications in the fields of image processing, pattern recognition, medical fields etc. In most image retrieval systems image is represented as a set of low level features. In this image retrieval paper comparative study is performed on color, texture and color-texture using various internal semantic properties using different methods. In this work texture features are extracted using Gray Level Co-occurrence Matrix (GLCM) for texture feature extraction. The images are retrieved according to user satisfaction and thereby reduce the semantic gap between low level features and high level features. Again Color features are extracted using RGB, DCT and HSV methods and compared. Finally In this paper texture features and color features are combined to check the precision and recall rates for all methods.

Keywords- CBIR, TEXTURE-GLCM, COLOR-HSV, DCT, PRECISION, RECALL
Publication Details
Unique Identification Number - IJEDR1804044
Page Number(s) - 243-247
Pubished in - Volume 6 | Issue 4 | November 2018
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Ramya Nagaraju Gowda,  Vinodha H N,   "Comparative Study on Image Retrieval using Color, Texture and Color-Texture, Based on Semantic Properties", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 4, pp.243-247, November 2018, Available at :http://www.ijedr.org/papers/IJEDR1804044.pdf
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