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Multi-Query Content Based Image Retrieval System using Local Binary Patterns
Author(s) -
Simily Joseph,
Kannan Balakrishnan
Publication year - 2011
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/2235-2857
Subject(s) - computer science , information retrieval , content based image retrieval , binary number , content (measure theory) , image retrieval , image (mathematics) , artificial intelligence , mathematics , mathematical analysis , arithmetic
Content Based Image Retrieval systems open new research areas in Computer Vision due to the high demand of image searching methods. CBIR is the process of finding relevant image from large collection of images using visual queries. The proposed system uses multiple image queries for finding desired images from database. The different queries are connected using logical AND operation. Local Binary Pattern (LBP) texture descriptors of the query images are extracted and those features are compared with the features of the images in the database for finding the desired images. The proposed system is used for retrieving similar human face expressions. The use of multiple queries reduces the semantic gap between low level visual features and high level user expectation. The experimental result shows that, the use of multiple queries has better retrieval performance over single image queries. General Terms Image Processing, Content Based Image Retrieval

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