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Proceedings Paper

Print image sharpness analysis based on gray-level co-occurrence matrices
Author(s): Lin Zhang; Meiyun Zhang; Yangyu Wu
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Paper 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.

Paper Details

Date Published: 19 August 2010
PDF: 7 pages
Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78201Q (19 August 2010); doi: 10.1117/12.866719
Show Author Affiliations
Lin Zhang, Shaanxi Univ. of Science and Technology (China)
Meiyun Zhang, Shaanxi Univ. of Science and Technology (China)
Yangyu Wu, Shaanxi Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7820:
International Conference on Image Processing and Pattern Recognition in Industrial Engineering
Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du, Editor(s)

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