Markovian Algorithms for the Gray Thresholding of Machine Vision -- Application in IC Wire-Bonding Process

• Main Author: 蔡裕正
• Other Authors: 陳文魁
• Format: Others
• Language: zh-TW
• Published: 1995
• Online Access: http://ndltd.ncl.edu.tw/handle/61949344983450744385

碩士 === 義守大學 === 管理科學研究所 === 83 === 　　Wire-bonding is one of critical processes that affect the quality of IC package. Nowadays the wire-bonder are all automatic and these machines are equipped well with Machine Vision either. With the indirect pad-positioning vision system. the bonding productivity depends heavily upon technology as well as techniques in pattern recognition. Even if the vision system is good at recognizing, the bonding capability is still strongly related to the "clearness" of the binary die image. 　　The binary die image in the wire bonding process is converted from its digital die image that according to the thresholding. Technically, all the various existing optimization methods, for the determination of thresholding, are not appropriate for the IC packaging industry since the digital images of die are not consistently similar even the same wafer. 　　In order to overcome the aforementioned positioning problem, this paper is to explore the stochastic features of the die images, and then to develop some robustic Markovian algorithms aided to pad-positioning both effectively and efficiently.