NDLI: A nonparametric statistical analysis of texture segmentation performance using a foveated image preprocessing similar to the human retina

Content Provider	IEEE Xplore Digital Library
Author	Kuyel, T. Ghosh, J. Geisler, W.
Copyright Year	1996
Description	Author affiliation: Centre for Vision & Image Sci., Texas Univ., Austin, TX, USA (Kuyel, T.; Ghosh, J.; Geisler, W.)
Abstract	The human visual system is "foveated" in nature. The foveated nature of the human retina can be considered as a visual resource allocation such that there is drastically varying resolution within the field of view. Here, texture segmentation using a retina-like foveated image preprocessor is performed and the texture segmentation performance is analyzed. Latest neurophysiological data from human and macaque retinae are used to determine the parameters of the foveated system. Texture patterns are artificially generated and are passed through the foveated preprocessor. Texture segmentation is done at the output of the foveated module using texture patch classification. At the classification stage, a near-optimal classifier is used with no data reduction or feature extraction stages, so that any change in the segmentation performance is solely due to the effects of visual eccentricity. Texture segmentation performance results with varying eccentricity are obtained. The performance is above human performance and smoothly drops with increasing eccentricity. This study demonstrates the importance of finding the minimum visual resolution which is required to do texture segmentation when a desired performance level is given. 'Sufficient resolution classification' may improve segmentation speeds considerably. From the authors' experiments, it has also been found out that a strong correlation exists between the human visual performance and the performance of the authors' artificial foveated visual system.
Starting Page	207
Ending Page	212
File Size	1677387
Page Count	6
File Format	PDF
ISBN	0780332008
DOI	10.1109/IAI.1996.493754
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-04-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Statistical analysis Humans Image segmentation Visual system Retina Resource management Image analysis Image texture analysis Performance analysis Feature extraction
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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