Journal Paper

Paper Title - Content Based Image Retrival Using Different Clustering Techniques


Abstract
CBIR (Content based image retrieval) is the software system for retrieving the images from the database by using their features. In CBIR technique, the images are retrieved from the dataset by using the features like color, text, shape, texture and similarity. Object recognition technique is used in CBIR. Research on multimedia systems and content-based image retrieval is given tremendous importance during the last decade. The reason behind this is the fact that multimedia databases handle text, audio, video and image information, which are of prime interest in web and other high end user applications. Content-based Image retrieval deals with the extraction of knowledge, image data relationship, or other patterns not expressly keep within the pictures. It uses ways from computer vision, image processing, image retrieval, data retrieval, machine learning, database and artificial intelligence. Rule retrieval has been applied to large image databases. The proposed system gives average accuracy of 90%. Keywords— CBIR, Color feature, Shape feature, Texture feature, Feature extraction, Clustering, Image Retrieval.


Author - Mahadev A. More, M.M. Patil

Citation - Mahadev A. More   ,   M.M. Patil   ,   Mahadev A. More, M.M. Patil " Content Based Image Retrival Using Different Clustering Techniques " , International Journal of Industrial Electronics and Electrical Engineering , Volume-4,Issue-7  ( Jul, 2016 )

Indexed - Google Scholar


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| Published on 2016-08-12