Swift perspective shape matching algorithm based on Phong's model for FPC stiffener bonding systems. Issue 4 (28th October 2014)

• Record Type: Journal Article
• Authors: Su, Ye; Yutang, Ye; Yu, Xie; Maoli, Yi; Jing, Zhang; Ying, Luo; Chunlei, Du
• Is Part Of: Circuit world. Volume 40:Issue 4(2014)
• Page Start: 141
• Page End: 149
• Publication Date: 2014-10-28
• Subjects: Electronic circuits -- Design and construction -- Periodicals; Electronic circuits -- Periodicals; 621.381505
• DOI: 10.1108/CW-06-2014-0023
• Languages: English
• ISSNs: 0305-6120

Abstract

<abstract> <title> <x content-type="archive" xml:space="preserve">Abstract</x> </title> <sec> <title content-type="abstract-heading">Purpose</title> <p> – This paper aims to solve the issue of target positioning in auto stiffener bonder (ASB) systems for flexible printed circuits. </p> </sec> <sec> <title content-type="abstract-heading">Design/methodology/approach</title> <p> – The proposed approach uses Phong's bidirectional reflectance distribution function (BRDF) model to simulate the reflection of light off a target in ASB systems to predict the current pose of the target based on image brightness, update the template, decrease the initial errors in the template and narrow down the search range. </p> </sec> <sec> <title content-type="abstract-heading">Findings</title> <p> – The experimental results indicate that the proposed approach can predict the inclination angle of the target with precision, presenting angle prediction errors of less than three degrees. Furthermore, with larger inclined angles, the overall matching errors were less than 1.5 pixels. Comparisons with the unmodified matching algorithm revealed that the proposed approach resulted in 65 per cent less calculation time for the algorithm and 14 per cent higher overall work efficiency in the ASB system. </p> </sec> <sec> <title content-type="abstract-heading">Originality/value</title> <p> – The edge-based perspective shape matching algorithm was modified using the Phong BRDF model and enhanced algorithm efficiency with the target pose prediction method while ensuring the precision and robustness of the system. The proposed approach has high potential value and can be expanded to recognition systems for objects with varying inclination angles and highly reflective surfaces.</p> </sec> </abstract>