Structural filtering with texture feature-based interaction maps: Fast algorithm and applications

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

We have recently introduced a new tool for texture analysis called feature based interaction map (FBIM). The FBIM approach can be efficiently used to assess fundamental structural properties of textures such as anisotropy, symmetry, orientation and regularity. The FBIM is suitable for rotation-invariant texture classification of patterns with regular, weak regular, or linear structure. In this paper, we show how the interaction map can be applied as a structural filter for segmentation, detection of textured objects and texture defects, analysis of oriented structures and shape-from-texture. The power of the FBIM filter is in its unique capability to grasp the structure of pixel interactions typical for a given texture pattern. To efficiently use this capability, we propose a fast running implementation of the FBIM algorithm and present pilot experimental results demonstrating the potential of the FBIM approach in diverse tasks and applications.

Original languageEnglish
Title of host publicationTrack B
Subtitle of host publicationPattern Recognition and Signal Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages795-799
Number of pages5
ISBN (Print)081867282X, 9780818672828
DOIs
Publication statusPublished - Jan 1 1996
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: Aug 25 1996Aug 29 1996

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Other

Other13th International Conference on Pattern Recognition, ICPR 1996
CountryAustria
CityVienna
Period8/25/968/29/96

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Chetverikov, D. (1996). Structural filtering with texture feature-based interaction maps: Fast algorithm and applications. In Track B: Pattern Recognition and Signal Analysis (pp. 795-799). [546932] (Proceedings - International Conference on Pattern Recognition; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPR.1996.546932