Effect of gray-level re-quantization on co-occurrence based texture analysis

Mehul B. Patel; Jeffrey J. Rodriguez; Arthur F. Gmitro

doi:10.1109/ICIP.2008.4711822

Effect of gray-level re-quantization on co-occurrence based texture analysis

Mehul B. Patel, Jeffrey J. Rodriguez, Arthur F. Gmitro

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Scopus citations

Abstract

Gray-level co-occurrence matrices (GLCM) are widely used for texture analysis. The number of gray-levels used while computing GLCM is an important parameter but is often ignored. It is believed that the higher the number of gray-levels used, the better is the performance of the GLCM-based features. Contrary to this belief, we observed that using more gray levels than the actual range of pixel values in the image can give erroneous results. In this paper, we show how this occurs and discuss a way around this problem.

Original language	English (US)
Title of host publication	2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings
Pages	585-588
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2008.4711822
State	Published - 2008
Event	2008 IEEE International Conference on Image Processing, ICIP 2008 - San Diego, CA, United States Duration: Oct 12 2008 → Oct 15 2008

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
ISSN (Print)	1522-4880

Other

Other	2008 IEEE International Conference on Image Processing, ICIP 2008
Country/Territory	United States
City	San Diego, CA
Period	10/12/08 → 10/15/08

Keywords

Gray-level co-occurrence matrix
Histogram
Re-quantization
Texture analysis

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

Access to Document

10.1109/ICIP.2008.4711822

Cite this

Effect of gray-level re-quantization on co-occurrence based texture analysis. / Patel, Mehul B.; Rodriguez, Jeffrey J.; Gmitro, Arthur F.
2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings. 2008. p. 585-588 4711822 (Proceedings - International Conference on Image Processing, ICIP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Patel, MB, Rodriguez, JJ & Gmitro, AF 2008, Effect of gray-level re-quantization on co-occurrence based texture analysis. in 2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings., 4711822, Proceedings - International Conference on Image Processing, ICIP, pp. 585-588, 2008 IEEE International Conference on Image Processing, ICIP 2008, San Diego, CA, United States, 10/12/08. https://doi.org/10.1109/ICIP.2008.4711822

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abstract = "Gray-level co-occurrence matrices (GLCM) are widely used for texture analysis. The number of gray-levels used while computing GLCM is an important parameter but is often ignored. It is believed that the higher the number of gray-levels used, the better is the performance of the GLCM-based features. Contrary to this belief, we observed that using more gray levels than the actual range of pixel values in the image can give erroneous results. In this paper, we show how this occurs and discuss a way around this problem.",

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Effect of gray-level re-quantization on co-occurrence based texture analysis

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

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