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Proceedings Paper

Multiple channel surface orientation from texture
Author(s): Nanda Gopal; Alan Conrad Bovik; Joydeep Ghosh
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Paper Abstract

This paper studies the computation of surface orientation by analyzing the responses of multiple spatio-spectrally localized channel filters. Images containing textures that encode information about local surface orientation are decomposed into narrowband sub-images possessing characteristic radial frequency and orientation properties. By analyzing the spatial variation in the filter responses, information about the spatial variation in the pattern I texture can be elucidated and subsequently used to estimate surface orientation. The channel filters used are Gaborfunctions, which have previously been applied successfully to related problems in texture analysis, segmentation, and characterization. The Gabor functions are plausible approximations to the responses of the highly oriented simple cells in mammalian striate cortex. They also possess important properties for the local isolation and characterization of textures. In our approach, texture gradients are modeled as giving rise to pattern frequency gradients that can be exiracted on a highly localized basis. A variational optimization procedure for estimating the pattern frequency variation is implemented via a discrete relaxation procedure that is suitable for a massively parallel computation. The result of the optimization procedure is a stable dense map describing the localized image frequency content. The computed image frequency characteristics are then used to define a texture density measure used in a planar-surface approximation procedure, yielding slant/tilt estimates describing the surface orientation. Experimental results support the theoretical derivations.

Paper Details

Date Published: 1 October 1990
PDF: 10 pages
Proc. SPIE 1249, Human Vision and Electronic Imaging: Models, Methods, and Applications, (1 October 1990); doi: 10.1117/12.19690
Show Author Affiliations
Nanda Gopal, Univ. of Texas/Austin (United States)
Alan Conrad Bovik, Univ. of Texas/Austin (United States)
Joydeep Ghosh, Univ. of Texas/Austin (United States)

Published in SPIE Proceedings Vol. 1249:
Human Vision and Electronic Imaging: Models, Methods, and Applications
Bernice E. Rogowitz; Jan P. Allebach, Editor(s)

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