- 期刊
球格陣列(BGA)基板表面瑕疵檢測
A Non-Referential Machine Vision Approach for BGA Substrate Inspection
摘要
本研究主要利用機器視覺技術檢測球格陣列(BGA)基板表面之瑕疵。針對BGA基板之邊緣輪廓具規律性的特性，採用規則設計法(Design-rule)將BGA基板上具規律性的基本組成去除。由於待測BGA基板影像的「基本組成」圖案單純，僅由直線及圓弧等圖案組成，因此基於去除基本組成即可凸顯異常瑕疵的概念，本研究設計去除規律性圖案的限制規則，將符合BGA板上已知設計條件的基本組成圖形去除，主要方法乃利用霍氏轉換(Hough transform)及相關度指標來偵測這些基本組成圖形，並配合為去除規律性圖形所設計的幾何限制規則(Constraint rules)，來消除待測影像中具「規則性」的基本組成圖形，以有效凸顯不規律的異常區塊，此方法可免除傳統樣板比對(Template matching)易受環境變異影響的缺失。
並列摘要
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.