Content Based Image Retrieval using Texture, Color and Shape for Image Analysis
DOI:
https://doi.org/10.24297/ijct.v3i1c.2768Keywords:
Low level features, Gray Level Cooccurence Matrix(GLCM), Histogram, Shape features, Precision, Recall, AccuracyAbstract
Content- Based Image Retrieval(CBIR) or QBIR is the important field of research..Content Based Image retrieval has gained much popularity in the past Content-based image retrieval (CBIR)[1] system has also helped users to retrieve relevant images based on their contents. It represents low level features like texture ,color and shape .In this paper, we compare the several feature extraction techniques [5]i.e..GLCM ,Histogram and shape properties over color, texture and shape The experiments show the similarity between these features and also that the output obtained using this combination of color, texture and shape is better as obtaining output with a single feature
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Published
2012-08-01
How to Cite
Sandhu, A., & Kochhar, A. (2012). Content Based Image Retrieval using Texture, Color and Shape for Image Analysis. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 3(1), 149–152. https://doi.org/10.24297/ijct.v3i1c.2768
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Research Articles
