R
R. Balasubramanian
Researcher at Indian Institute of Technology Roorkee
Publications - 11
Citations - 1260
R. Balasubramanian is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: Content-based image retrieval & Image retrieval. The author has an hindex of 7, co-authored 11 publications receiving 1157 citations.
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Local Tetra Patterns: A New Feature Descriptor for Content-Based Image Retrieval
TL;DR: A novel image indexing and retrieval algorithm using local tetra patterns (LTrPs) for content-based image retrieval (CBIR) that encodes the relationship between the referenced pixel and its neighbors, based on the directions that are calculated using the first-order derivatives in vertical and horizontal directions.
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Local maximum edge binary patterns: A new descriptor for image retrieval and object tracking
TL;DR: A new algorithm meant for content based image retrieval (CBIR) and object tracking applications is presented, which differs from the existing LBP in a manner that it extracts the information based on distribution of edges in an image.
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Directional local extrema patterns: a new descriptor for content based image retrieval
TL;DR: A new algorithm using directional local extrema patterns meant for content-based image retrieval application that shows a significant improvement in terms of their evaluation measures as compared with other existing methods on respective databases.
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Directional Binary Wavelet Patterns for Biomedical Image Indexing and Retrieval
TL;DR: A new algorithm for medical image retrieval which shows a significant improvement in terms of their evaluation measures as compared to LBP and LBP with Gabor transform is presented.
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Expert system design using wavelet and color vocabulary trees for image retrieval
TL;DR: A new image indexing and retrieval system for content based image retrieval (CBIR) is proposed and shows a significant improvement in terms of average precision, average recall and average retrieval rate on DB1 database and average retrieved rate on texture databases as compared with most of existing techniques on respective databases.