Multi-level 3-D rotational invariant classification

R. L. Kashyap, Y. Choe

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


A two-level 3-D rotational invariant classification is developed based on Fractional Differencing model. In first level, classification has been done with a fractal scale, and in second level, textures have been classified further in detail with the additional frequency parameters. Because of the properties of the fractal scale and multi-level procedure, the proposed 3-D rotational invariant classification scheme reduces the processing time and gives enough accuracy of the classification simultaneously. As a result of a series of experiments involving the differently oriented samples of natural textures, it is concluded that these combined features make possible for this multi-level classification method to have a strong class separability power for arbitrary oriented 3-D texture patterns.

Original languageEnglish
Title of host publicationConference B
Subtitle of host publicationPattern Recognition Methodology and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Print)0818629150
Publication statusPublished - 1992
Event11th IAPR International Conference on Pattern Recognition, IAPR 1992 - The Hague, Netherlands
Duration: 1992 Aug 301992 Sept 3

Publication series

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


Conference11th IAPR International Conference on Pattern Recognition, IAPR 1992
CityThe Hague

Bibliographical note

Publisher Copyright:
© 1992 Institute of Electrical and Electronics Engineers Inc. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition


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