An Application of Color Images for Leadframe Quality Inspection

• Main Authors: Tsung-Wei Li, 李崇偉
• Other Authors: Du-Ming Tsai
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/39028777916291139386

碩士 === 元智大學 === 工業工程研究所 === 86 === The purpose of this research is to inspect coppery surfaces of transisitor and LED leadframes in the electroplated process using color machine vision. Defects on coppery surfaces include oxygenation and various types of contamination, which are very difficult to detect in a gray-level image. A color image holds a richer information than the gray-level one. Color images may be represented by various set of coordinat es for the description of color characteristics such as hue, saturation and brightness. In this research, 31distinct color features from 13 existing color models have been investigated. Bays classifier is used to distinguish between defect and non-defect surfaces of leadframes. The best combination of color features used in the Bayes classifier is selected using a bottom-up stepwise search procedure. Both constant lighting and varying lighting that simulates the decay of illumination in industry environments are considered, and their corresponding color feature sets for best discriminating surface defects are determined. The performance of the proposed method is evaluated by segmenting defects in color images. Experimental results have shown that Bayes classifier with multiple color features has better discrimination than that with single gray-level feature.