Content Based Image Retrieval using interactive genetic algorithm

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Vinee V. Kawade; Arti V. Bang: Content Based Image Retrieval using interactive genetic algorithm. 2014 Annual IEEE India Conference (INDICON), 1 - 6.



Large amounts of databases are created due to the developments in data storage and acquisition technologies. There is a need to develop an appropriate system that will manage these entire databases. Also we need to precisely and effectively retrieve images from these databases for various applications. The Content Based Image Retrieval (CBIR) system serves this purpose. In this paper, we introduce a user based system for CBIR in which genetic algorithm is applied. The different features of color image such as mean, standard deviation and the image bitmap are used for retrieval. In addition, the texture features such as the edge histogram of an image and the entropy of the gray level co-occurrence matrix are used. Furthermore, the genetic algorithm is applied to help the user in identifying the images which satisfy his needs for reducing the gap between the users' expectation and the retrieval results.

Extended Abstract


author={V. V. Kawade and A. V. Bang},
booktitle={2014 Annual IEEE India Conference (INDICON)},
title={Content Based Image Retrieval using interactive genetic algorithm},
keywords={content-based retrieval;entropy;genetic algorithms;image colour analysis;image retrieval;image texture;CBIR;color image features;content based image retrieval;gray level co-occurrence matrix entropy;image bitmap;image edge histogram;image texture features;interactive genetic algorithm;user based system;Genetic algorithms;Image color analysis;Image edge detection;Image retrieval;Sociology;Statistics;Content based image retrieval;gray level co-occurrence matrix;low level features},
url={ },

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