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Article Dans Une Revue International Journal of Virtual Reality Année : 2015

Image Texture Feature Extraction Method Based on Regional Average Binary Gray Level Difference Co-occurrence Matrix

Résumé

Texture feature is a measure method about relationship among the pixels in local area, reflecting the changes of image space gray levels. This paper presents a texture feature extraction method based on regional average binary gray level difference co-occurrence matrix, which combined the texture structural analysis method with statistical method. Firstly, we calculate the average binary gray level difference of eight-neighbors of a pixel to get the average binary gray level difference image which expresses the variation pattern of the regional gray levels. Secondly, the regional co-occurrence matrix is constructed by using these average binary gray level differences. Finally, we extract the second-order statistic parameters reflecting the image texture feature from the regional co-occurrence matrix. Theoretical analysis and experimental results show that the image texture feature extraction method has certain accuracy and validity
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Dates et versions

hal-01530561 , version 1 (31-05-2017)

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  • HAL Id : hal-01530561 , version 1

Citer

Jian Yang, Jingfeng Guo. Image Texture Feature Extraction Method Based on Regional Average Binary Gray Level Difference Co-occurrence Matrix. International Journal of Virtual Reality, 2015, 10 (3), pp.73-79. ⟨hal-01530561⟩

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