Content Based Image Retrieval Using Color, Texture and Shape: A Review

Authors

DOI:

https://doi.org/10.18486/ijcsnt/12.1.156

Keywords:

Content Based Image Retrieval, Feature Extraction, Color, Texture, Shape

Abstract

 Image Retrieval system is an efficient and satisfactory tool for organizing huge image databases. Basically, image retrieval is based not on interpretations or keywords, but basically based on features derive straight from the image statistics. Content based image retrieval (CBIR) is found of retrieving the utmost visibly identical images to a given query image from a database of images. In CBIR, low level features are extracted based on their visual content which is Color, Texture & Shape. In other words, we can describe that the information which is derived about color, texture and shape from an image is called image features. In this paper two features are used for retrieving the images such as Color and Texture. Color feature is extracted by using different color space such as RGB, HSV, YCbCr, and CMY. Texture feature is extracted by applying the statistical methods such as Mean, Standard Deviation, Skewness and GLCM.  

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Published

2023-04-30

How to Cite

Content Based Image Retrieval Using Color, Texture and Shape: A Review. (2023). International Journal of Communication Systems and Network Technologies, 12(1), 01-16. https://doi.org/10.18486/ijcsnt/12.1.156