Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/395043
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dc.contributor.authorJing Yi Tou-
dc.contributor.authorYong Haur Tay-
dc.contributor.authorPhooi Yee Lau-
dc.date.accessioned2023-06-15T07:54:12Z-
dc.date.available2023-06-15T07:54:12Z-
dc.identifier.otherukmvital:122780-
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/395043-
dc.description.abstractThe Grey-level Co-occurrence Matrices (GLCM) has been widely used for various texture analysis implementations and has provided satisfying results. The conventional GLCM method is two dimensional as it focus on the co-occurrence of the specific pixel pairs. The one-dimensional GLCM reduces the matrices to a single dimension by focusing only on the differences of the grey level between pixel pairs. The experiment results on 32 Brodatz textures shows that in a same setting, the one-dimensional GLCM achieved a recognition rate of 83.01 % while the conventional GLCM achieved a recognition rate of 81.35%. The results show that the one-dimensional GLCM can perform as good as the conventional GLCM but with fewer computations involved.-
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE),Piscataway, US-
dc.subjectOne-dimensional grey-level (GLCM)-
dc.subjectTexture classification-
dc.titleOne-dimensional grey-level co-occurrence matrices for texture classification-
dc.typeSeminar Papers-
dc.format.pages6-
dc.identifier.callnoT58.5.C634 2008 kat sem j.3-
dc.contributor.conferencenameInternational Symposium on Information Technology-
dc.coverage.conferencelocationKuala Lumpur Convention Centre-
dc.date.conferencedate26/08/2008-
Appears in Collections:Seminar Papers/ Proceedings / Kertas Kerja Seminar/ Prosiding

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