自動化IC印字瑕疵檢測(Ⅱ)-瑕疵辨識

本研究主要針對IC印字部份建構出一套瑕疵檢測系統，此系統主要可分成前處理及瑕疵檢測兩大部份。在前處理部份，主要包含待測影像之影像二值化、影像旋轉、影像切割以及影像細線化等前置處理。在瑕疵檢測部份，包含字元搜尋、特徵值擷取、特徵值比對或影像比對以及瑕疵辨識等處理。在成效上，本瑕疵檢測系統可順利辨認出常見的七項IC印字瑕疵。就一顆構裝尺寸為15mm及8mm內含16印字IC為例，辨認速度達0.54IC／秒，良品檢測精確度達99.5%，檢測瑕疵精確度達98.25%。另外，本研究提出粗略與精細字元搜尋法，比傳統之投影式影像分割法快且易於分割字元。同時，當無需辨識瑕疵種類時，則搭配字元搜尋相關匹配法遠比遞迴投影分割相關匹配法好；當需辨識瑕疵種類時，本研究所提出之特徵比對法亦明顯優於遞迴投影分割相關匹配法。

關鍵字

IC印字；瑕疵辨識；相關匹配法

並列摘要

The study develops a defect detection system for the IC printed marks. The system can be divided into two main parts, namely, image pre-processing and defect detection. Image pre-processing includes binary image operation, image rotation, image segmentation and thinning operation. Defect detection includes character searching, characteristic extraction, characteristic comparison, image mapping and defect identification. As for the performance of this system, it can recognize the seven kinds of most common IC printed mark defects For a case of 15mm and 8mm IC chip with 16 printed marks, the recognition speed averages about 0.54 seconds for each chip, and the accuracy is 99.5% for distinguishing a good/bad chip and 98.25% for distinguishing the defect types. In addition, the study proposes a two-stage character searching method, which is quicker than the image projection and segmentation method. Moreover, when the defect types do not need to be distinguished, the research suggests the character searching method coupling with the normalized cross correlation scheme; however, when distinguishing the defect types is necessary, the study proposes the characteristic comparison method. Both have the better results.

並列關鍵字

IC printed mark ； defect detection ； normalized cross correlation

參考文獻

Ahmed, P.,Suen, C. Y.(1987).Computer Recognition of Totally Unconstrained Handwritten Zip Codes.International Journal of Pattern Recognition and Artificial Intelligence.1

Google Scholar

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