矽晶柱氧化疊差（OISF）之自動視覺檢驗

• Main Authors: Chia-Ling Chen, 陳佳玲
• Other Authors: Du-Ming Tsai
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/72124146342291048116

碩士 === 元智大學 === 工業工程研究所 === 89 === Oxidation Induce Stacking Fault (OISF) is frequently inspected in the crystal growing process of semiconductor industry. The appearance of OISF has “bar” and “half-moon” types that are mainly produced in crystal growth and silicon crystal post-manufacturing process. OISF image are generally enlarged by an optical electron microscope, and the density measure (total number of vertical and horizontal OISFs in a unit area) is manually obtained by a specially trained inspector. Number counting is a tiresome task, and very subjective from inspector to inspector. In this research we use machine vision to automatically compute the density measures of both “bar” and “half-moon” OISFs in a crystal surface. The inspection quality and time can be greatly improved with the automated visual inspection system. This research uses Sobel edge operator and wavelet frame to separate vertical and horizontal edges of “bar” and “half-moon” OISFs in a image. The number of horizontal and vertical OISFs in each separated image can be easily evaluated accordingly. Experimental results have shown that the average error of the proposed method is smaller than 5%, which is competitive with human inspectors.