A taxonomy for texture description and identification
A taxonomy for texture description and identification
Feature-based correspondence: an eigenvector approach
Image and Vision Computing - Special issue: BMVC 1991
Design and evaluation of algorithms for image retrieval by spatial similarity
ACM Transactions on Information Systems (TOIS)
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
Content based image retrieval and information theroy: a general approach
Journal of the American Society for Information Science and Technology - Visual based retrieval systems and web mining
Informaton theoretic similarity measures for content based image retrieval
Journal of the American Society for Information Science and Technology - Visual based retrieval systems and web mining
Robot Vision
Modern Information Retrieval
Query by Visual Example - Content based Image Retrieval
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
On computing global similarity in images
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Outex - New Framework for Empirical Evaluation of Texture Analysis Algorithms
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Correspondence Matching with Modal Clusters
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper presents an effective texture descriptor invariant to translation, scaling, and rotation for texture-based image retrieval applications. The proposed texture descriptor is built taking the Fourier space of the image. In order to find the best texture descriptor, a quantization scheme based on Lloyd's technique is proposed. As frequency descriptors are not invariant to all geometrical transformations as scaling and rotation, the modal analysis is applied to overcome these problems. Our image database is extracted from Brodatz album as well other sources. The proposed method is also compared with other content-based techniques and their performance is evaluated through several experiments. The effectiveness of both methods is measured by the commonly used retrieval performance measurement – Precision and Recall.