Wold Features for Unsupervised Texture Segmentation
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
On the convergence of image compression and object recognition
Proceedings of the 43rd annual Southeast regional conference - Volume 2
An evolutionary system for near-regular texture synthesis
Pattern Recognition
Segmentation and retrieval of ancient graphic documents
GREC'05 Proceedings of the 6th international conference on Graphics Recognition: ten Years Review and Future Perspectives
Structured representations in a content based image retrieval context
Journal of Visual Communication and Image Representation
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A novel approach for coding textured images is presented. The texture field is assumed to be a realization of a regular homogeneous random field, which can have a mixed spectral distribution. On the basis of a two-dimensional (2-D) Wold-like decomposition, the field is represented as a sum of a purely indeterministic, harmonic, and countable number of evanescent fields. We present an algorithm for estimating and coding the texture model parameters, and show that the suggested algorithm yields high-quality reconstructions at low bit rates. The model and the resulting coding algorithm are seen to be applicable to a wide variety of texture types found in natural images