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Volume 19 (2022)
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Advances in Computer Science and Engineering
Advances in Computer Science and Engineering
Volume 2, Issue 1, Pages 83 - 96 (March 2008)
MEDICAL IMAGE RETRIEVAL USING MOMENT-BASED SHAPE DESCRIPTORS
A. Grace Selvarani (India) and S. Annadurai (India)
Abstract:
Content-Based Image Retrieval (CBIR) has been one of the most vivid research areas in the field of computer vision, and substantial progress has been made over the last years. Efficient content-based image retrieval in the medical domain is still a challenging problem. CBIR systems are currently being integrated with picture archiving and communication systems for increasing the overall search capabilities and tools available for radiologists. Shape is one of the fundamental visual features in content-based medical image retrieval. A suitable shape based retrieval system must represent shapes in low dimension, be invariant to rotation, translation, and scale transforms and retrieve similar images that are relevant to the queries. This paper describes the study and evaluation of five region-based moment shape descriptors: Invariant moments, Zernike moments, Pseudo-Zernike moments, Legendre moments, Radial Chebyshev moments. The retrieval performances of the different shape descriptors are tested using a large medical image database and measured using commonly used performance measurement.
Keywords and phrases:
CBIR, invariant moments, Zernike moments, Pseudo-Zernike moments, Radial Chebyshev moments, Legendre moments, precision and recall.
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