Adaptive thresholding based on co-occurrence matrix edge information
In this paper, an adaptive thresholding technique based on gray level co-occurrence matrix (GLCM) is presented to handle images with fuzzy boundaries. As GLCM contains information on the distribution of gray level transition frequency and edge information, it is very useful for the computation of t...
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my.utm.86002009-07-27T03:35:55Z http://eprints.utm.my/id/eprint/8600/ Adaptive thresholding based on co-occurrence matrix edge information Mohd. Mokji, Musa Syed Abu Bakar, Syed Abdul Rahman TK Electrical engineering. Electronics Nuclear engineering In this paper, an adaptive thresholding technique based on gray level co-occurrence matrix (GLCM) is presented to handle images with fuzzy boundaries. As GLCM contains information on the distribution of gray level transition frequency and edge information, it is very useful for the computation of threshold value. Here the algorithm is designed to have flexibility on the edge definition so that it can handle the object’s fuzzy boundaries. By manipulating information in the GLCM, a statistical feature is derived to act as the threshold value for the image segmentation process. The proposed method is tested with the starfruit defect images. To demonstrate the ability of the proposed method, experimental results are compared with three other thresholding techniques. 2007 Conference or Workshop Item PeerReviewed Mohd. Mokji, Musa and Syed Abu Bakar, Syed Abdul Rahman (2007) Adaptive thresholding based on co-occurrence matrix edge information. In: International Conference on Asia Modelling Symposion, 27-30 March 2007, Phuket. http://dx.doi.org/10.1109/AMS.2007.8 |
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TK Electrical engineering. Electronics Nuclear engineering Mohd. Mokji, Musa Syed Abu Bakar, Syed Abdul Rahman Adaptive thresholding based on co-occurrence matrix edge information |
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In this paper, an adaptive thresholding technique based on gray level co-occurrence matrix (GLCM) is presented to handle images with fuzzy boundaries. As GLCM contains information on the distribution of gray level transition frequency and edge information, it is very useful for the
computation of threshold value. Here the algorithm is designed to have flexibility on the edge definition so that it can handle the object’s fuzzy boundaries. By manipulating information in the GLCM, a statistical feature is derived to act as the threshold value for the image segmentation process. The proposed method is tested with the starfruit defect images. To demonstrate the ability of the proposed method, experimental results are compared with three other thresholding techniques. |
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Conference or Workshop Item |
author |
Mohd. Mokji, Musa Syed Abu Bakar, Syed Abdul Rahman |
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Mohd. Mokji, Musa Syed Abu Bakar, Syed Abdul Rahman |
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Mohd. Mokji, Musa |
title |
Adaptive thresholding based on co-occurrence matrix edge information |
title_short |
Adaptive thresholding based on co-occurrence matrix edge information |
title_full |
Adaptive thresholding based on co-occurrence matrix edge information |
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Adaptive thresholding based on co-occurrence matrix edge information |
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Adaptive thresholding based on co-occurrence matrix edge information |
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adaptive thresholding based on co-occurrence matrix edge information |
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2007 |
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http://eprints.utm.my/id/eprint/8600/ http://dx.doi.org/10.1109/AMS.2007.8 |
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