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An enhanced shape descriptor based on radial distances

Contour and region based descriptors are among the main approaches in content based image retrieval (CBIR). In the contour based approaches, Fourier Transform is applied on the shape signatures to obtain Fourier descriptors (FD), which has attractive properties such as rotational, scale, and transla...

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Bibliographic Details
Main Authors: Tiagrajah V.J., Razeen A.A.S.M.
Other Authors: 35198314400
Format: Conference paper
Published: 2023
Subjects:
CBIR
Fourier descriptors
Retrieval
Shape
Content based retrieval
Image processing
Content-Based Image Retrieval
Data sets
Descriptors
Radial distance
Region-based
Retrieval performance
Shape descriptors
Shape signatures
Translational invariance
Finite difference method
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Summary:Contour and region based descriptors are among the main approaches in content based image retrieval (CBIR). In the contour based approaches, Fourier Transform is applied on the shape signatures to obtain Fourier descriptors (FD), which has attractive properties such as rotational, scale, and translational invariance. However, the FD derived from different signatures can have significant effect on the performance of retrieval. In this paper we introduce a new shape signature, which is called the radial distance with triangular centroid area (RDTCA) signature. Based on our retrieval experiments using Kimia 99 and Kimia 216 dataset, FD derived from RDTCA signature outperformed the FD derived from other signatures in terms of robustness and retrieval performance. � 2011 IEEE.

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