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A Multiple Threshold Selection Algorithm Based on Maximum Fuzzy Entropy for the Final Inspection of Flip Chip BGA  

김경범 (국립충주대학교 기계설계학과)
Publication Information
Journal of the Korean Society for Precision Engineering / v.21, no.4, 2004 , pp. 202-209 More about this Journal
Abstract
Quality control is essential to the final product in BGA-type PCB fabrication. So, many automatic vision systems have been developed to achieve speedy, low cost and high quality inspection. A multiple threshold selection algorithm is a very important technique for machine vision based inspection. In this paper, an inspected image is modeled by using fuzzy sets and then the parameters of specified membership functions are estimated to be in maximum fuzzy entropy with the probability of the fuzzy sets, using the exhausted search method. Fuzzy c-partitions with the estimated parameters are automatically generated, and then multiple thresholds are selected as the crossover points of the fuzzy sets that form the estimated fuzzy partitions. Several experiments related to flip chip BGA images show that the proposed algorithm outperforms previous ones using both entropy and variance, and also can be successfully applied to AVI systems.
Keywords
Crossover points; Fuzzy set; Fuzzy c-partition; Maximum fuzzy entropy; Membership function; Multiple threshold;
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Times Cited By KSCI : 1  (Citation Analysis)
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