Casadei, Stefano and Mitter, Sanjoy and Perona, Pietro (1992) Boundary detection in piecewise homogeneous textured images. In: Second European Conference on Computer Vision — ECCV'92. Lecture Notes in Computer Science. No.588. Springer , New York, pp. 174-183. ISBN 978-3-540-55426-4. https://resolver.caltech.edu/CaltechAUTHORS:20140730-101725409
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Abstract
We address the problem of scale selection in texture analysis. Two different scale parameters, feature scale and statistical scale, are defined. Statistical scale is the size of the regions used to compute averages. We define the class of homogeneous random functions as a model of texture. A dishomogeneity function is defined and we prove that it has useful asymptotic properties in the limit of infinite statistical scale. We describe an algorithm for image partitioning which has performed well on piecewise homogeneous synthetic images. This algorithm is embedded in a redundant pyramid and does not require any ad-hoc information. It selects the optimal statistical scale at each location in the image.
| Item Type: | Book Section | |||||||||
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| Additional Information: | © Springer-Verlag Berlin Heidelberg 1992. Research supported by Airforce grant AFOSR-89-0276-C and ARO grant DAAL03-86-K-0171, Center for Intelligent Control Systems. | |||||||||
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| Subject Keywords: | Texture Analysis; Thermodynamic Limit; Statistical Scale; Boundary Detection; Image Descriptor | |||||||||
| Series Name: | Lecture Notes in Computer Science | |||||||||
| Issue or Number: | 588 | |||||||||
| DOI: | 10.1007/3-540-55426-2_20 | |||||||||
| Record Number: | CaltechAUTHORS:20140730-101725409 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20140730-101725409 | |||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
| ID Code: | 47666 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | Caroline Murphy | |||||||||
| Deposited On: | 05 Aug 2014 23:47 | |||||||||
| Last Modified: | 10 Nov 2021 17:48 |
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