球格陣列(BGA)基板表面瑕疵檢測

Abstract

In this research, a non-referential machine vision method is proposed to detect surface defects on ball grid array (BGA) substrates. Traditional automatic visual inspection systems have used template matching for PCB inspection. They require a large amount of memory storage, and suffer from environmental changes such as alignment, process variations, lighting, etc. Since the layout of BGA substrates is generally composed of basic primitives such as line segments, circular arcs, and other elements of regular shapes, the proposed method uses the Hough transform, similarity measures and geometric constraints to eliminate all regular primitives on BGA substrates. The remaining elements on the resulting image are those that have irregular shapes, and can be easily identified as defects. With the proposed approach, no reference template is required. It provides an efficient and flexible approach for automatic BGA defect inspection. Experimental results from more than 100 BGA substrate samples have shown the efficacy of the proposed method.