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19 August 2010 Print image sharpness analysis based on gray-level co-occurrence matrices
Lin Zhang, Meiyun Zhang, Yangyu Wu
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Proceedings Volume 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering; 78201Q (2010) https://doi.org/10.1117/12.866719
Event: International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 2010, Xi'an, China
Abstract
A novel measure is presented to quantify print image sharpness. Nine texture features of gray level co-occurrence matrices (GLCM) were calculated from the print images respectively which were blurred by Gaussian blurs filter with different radius ranging from 0 to 8 pixels in steps of 2. Experiments were performed on these images with different GLCM distance d (2, 4, 6, 8,10 pixels) and orientation θ (0°, 45°, 90°, 135°) under the constant window size (64 pixels). Furthermore, the correlation matrix of texture features was calculated to judge which texture features can be chosen to assess sharpness most. The test results show contrast and energy provide the most unique information of print image sharpness. And the distance d of GLCM can be determined to be 6 pixels and the different orientation θ has little effect on the trends. The method is reliable and extends GLCM with the sharpness evaluation of variable size, oriented print image.
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Lin Zhang, Meiyun Zhang, and Yangyu Wu "Print image sharpness analysis based on gray-level co-occurrence matrices", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78201Q (19 August 2010); https://doi.org/10.1117/12.866719
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KEYWORDS
Image analysis
Gaussian filters
Image filtering
Matrices
Image quality
Digital imaging
Statistical analysis
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