Paper
17 January 2005 Perception-based line quality measurement
Wencheng Wu, Edul N. Dalal
Author Affiliations +
Proceedings Volume 5668, Image Quality and System Performance II; (2005) https://doi.org/10.1117/12.585968
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
It is well-known that many sub-attributes of line quality contribute to the perception of the overall line quality. But the relative importance of these sub-attributes is not clear, nor is there a method available for combining them into one representative number for overall line quality. To address these issues, we have designed and conducted a series of psychophysical experiments, which explore the shape of the human visual transfer functions (VTF) relevant to the perception of three selected sub-attributes: lumpiness, waviness and raggedness. We found that human sensitivity to these sub-attributes can be represented by VTF’s of the same shape but with relative perception weighting factors of 6:4:3 respectively. Based on this, we have proposed an approach to assess overall line quality. In our method, we first pre-process the line image acquired and extract certain profiles relevant to line quality measurement. A set of corresponding VTF’s is then applied to these profiles to calculate the various sub-attributes. Finally, overall line quality is determined by the weighted combination of these individual sub-attributes. These preference weights (1:1:3 for lumpiness, waviness and raggedness respectively) are different from the perception weights mentioned earlier. Our preliminary results show that this measurement correlates well with human perception of overall line quality, for the sub-attributes studied.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wencheng Wu and Edul N. Dalal "Perception-based line quality measurement", Proc. SPIE 5668, Image Quality and System Performance II, (17 January 2005); https://doi.org/10.1117/12.585968
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Cited by 14 scholarly publications.
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KEYWORDS
Visualization

Data modeling

Quality measurement

Spatial frequencies

Image quality

Printing

Visual process modeling

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