臺灣博碩士論文加值系統

在自動化的視覺工業檢測系統中，影像處理技術一直左右著檢測系統的好壞。此篇論文中，針對X-Ray所拍攝到的多層印刷電路圖，以全自動的方式找出所有的圓孔資訊，並且以提出的模組化主動式輪廓偵測法增加擷取後結果的精確度。整個演算的流程主要可分為兩個部分：首先是對於印刷電路進行分析，找出可能為圓形的位置資訊，作為主動式輪廓偵測法的初始模組；然後將找出的初始模組，套入所提出的模組化主動式輪廓偵測法以增加其結果的精確度。在實驗分析中，雜訊20﹪以下的干擾，我們的方法可以有0.5 pixel的平均誤差。實際的 X-Ray影像之實驗結果已證實我們所提出之方法的可行性。最後並討論此方法的限制和未來發展的趨勢。

In the automatic optical inspection system, the performance is influenced by the adopted technology of image processing. In this thesis, we present a method to acquire whole information about circular holes automatically from the X-Ray image of a multi-layout printed circuit board（PCB）, and design a modular active contour to constraint the result close to the object. Two main stages desired in our approach include the segmentation of probably circular holes information and the accurate location of using modular active contour. The probably circular hole information are obtained by the analysis from the X-Ray image. Then, the probably circular hole information support the initial settings used in developed the modular active contour. According to the initial settings, modular active contour can carry out and push the initial model to locate closely the current circular hole. Experimental analyses have shown that the proposed approach obtains the performance of average error 0.5 pixel under 20% below random noise added. The experiments of real PCB images have also confirmed the feasibility of the proposed approach. Finally, the limitations and future works of the proposed method will also be discussed.

摘要 i
Abstract ii
誌謝 iii
目錄 iv
圖目錄 v
表目錄 vii
第一章 前言 1
1.1 研究目的 1
1.2 研究大綱 4
第二章 主動式輪廓偵測法（Active Contour） 5
2.1 影像擷取的介紹 5
2.2 傳統的主動式輪廓偵測法 7
2.3 充氣式輪廓偵測法 11
2.4 微分式階度輪廓偵測法 14
2.5 主動式輪廓偵測法的比較 17
第三章 方法描述（Proposed Approach） 18
3.1 方法流程概述 18
3.2 初始設定 21
3.3 肯尼邊緣偵測法 22
3.4 鏈碼編制 27
3.5 編號演算法 32
3.6 初始模組設定偵測 36
3.7 圓形化模組的主動式輪廓偵測法 42
第四章 實驗與分析討論 46
4.1 主動式輪廓偵測法的外部能量比較 46
4.2 主動式輪廓偵測法的實驗比較 49
4.3 加入模組化內部能量的主動式輪廓偵測法 53
4.4 實際X-Ray PCB影像的實驗 69
4.5 圓形初始模組設置的其他方法 77
4.6 實驗討論 79
第五章 結論 82
5.1 未來展望 82
5.2 結論 83
第六章 參考文獻 84

[1] M. Moganti, F. Ercal, “Automatic PCB Inspection System,” IEEE Potentials , Vol. 14, No. 3, 6-10,1995.
[2] G. Jacob, “Advances in Board Inspection,” Evaluation Engineering, 126-133, 1992.
[3] J. Bond, “Inspection Systems Distribute Test Throughout Manufacturing,” Test & Measurement World, 65-66, 1991.
[4] W. H. Schwartz, “Vision System for Pc Board Inspection,” Assembly Engineering, Vol. 29, No. 8, 18-21, 1986.
[5] D. T. Lee, “A Computerized Automatic Inspection System for Complex Printed Thick Film Patterns,” SPIE —Applications of Electronic Imaging systems, Vol.143, 172-177, 1978.
[6] A. Anzalone, M. Frucci, A. Machi, and G. Sanniti di Baja, “Parallel Implementation on a MIMD Machine of a PCB Computer Assisted Inspection Method,” 6th International Conference on Image Analysis and Processing: Progress in Image Analysis and Processing II, 679-687, 1991.
[7] M. Ito, and Y. Nikaido, “Recognition of Pattern Defects of Printed Circuit Board Using Topological Information,” Eleventh IEEE/CHMT International, Vol. 16, No. 18, 202-206, 1992.
[8] Y. Hara, H. Doi, K. Karasaki, and Tadashi Iida, “A System for PCB Automated Inspection Using Fluorescent Light,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-10, No.1, 1988.
[9] J. F. Borba, J. Facon, “A Printed Circuit Board Automated Inspection System,” Proceedings of the 38th Midwest Symposium on Circuits and Systems, Vol.1, 69-72, 1995.
[10] M. Mogant, and F. Ercal, “Segmentation of Printed Circuit Board Images Into Basic Patterns,” Computer Vision and Image Understanding, Vol. 70, No. 1, 74-86, 1998.
[11] M. Mogant, and F. Ercal, “A Sub-Pattern Level Inspection System for Printed Circuit Board,” Computer Vison and Image Understanding, Vol. 70, No. 1, 51-62, 1998.
[12] J. R. Mandeville, “Novel Method for Analysis of Printed Circuit Images,” IBM Journal of Research and Decelopment, Vol. 29, No.1, 73-87, 1985.
[13] J. W. Foster III, P. M. Griffin, S. L., Messimer, and J. ReneVillalobos, “Automated Visual Inspection of Bare Printed Circuit Boards,” Computers and industrial engineering, Vol. 18, No. 4, 493-504, 1990.
[14] Q. Z. Ye, and P. E. Danielson, “Inspection of Printed Circuit Boards by Connectivity Preserving Shrinking,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-10, No.5, 737-742, 1988.
[15] P. M. Griffin, J. R. Villalobos, J. W. Foster III, and S. L. Messimer, “Automated Visual Inspection of Bare Printed Circuit Boards,” Computers and Industrial Engineering, Vol. 18, No. 4, 505-509, 1990.
[16] B. Benhabib, C. R. Charette, K. C. Smith, and A. M. Yip, “Automatic Visual Inspection of Printed Circuit Board: An Experiment System,” International journal of Robotics and Automation, Vol. 5, No. 2, 1990.
[17] C. H. Yeh and D. M. Tsai, “Wavelet-Based Approach for Ball Grid Array (BGA) Substrate Conduct Paths Inspection,” International Journal of Production Research, Vol. 39, 4281-4299, 2001.
[18] D. M. Tsai and B. Hsiao, “Automatic Surface Inspection Using Wavelet Reconstruction,” Pattern Recognition, Vol. 34, 1285-1305, 2001.
[19] S. E. Hodges and R. J. Richards, “Fast Multi-Resolution Image Processing for PCB Manufacture,” Multiresolution Modelling and Analysis in Image Processing and Computer Vision, IEE , 1995.
[20] M. Kass, A. Witkin, and D. Terzopoulos, “Snakes - Active Contour Models,” International Journal of Computer Vision, Vol. 1, No. 4, 321-331, 1987.
[21] D. TerZopoulos. “On Matching Deformable Models to Image,” Optical Society of America, In Topical meeting on machine vision, Technical Digest Series, Volume 12, 160-163, 1987.
[22] L. D. Cohen., “On Active Contour Models and Balloons,” CVGIP Image Understanding, Vol. 53, No. 2, 211-218, 1991.
[23] C. Xu and J. L. Prince, “Gradient Vector Flow: A New External Force for Snakes,” IEEE Conference on Computer Vision and Pattern Recognition, 66-71, 1997.
[24] D. J. Williams, M. Shah, “A Fast Algorithm for Active Contours,” Computer Vision Proceedings, Third International Conference, 592 -595, 1990.
[25] K. M. Lam and H. Yan, “Fast Greedy Algorithm for Active Contours,” IEEE Electronics Letters, vol. 30, No.1, 21-23, 1994.
[26] C. Davatzikos and J. L. Prince. “An Active Contour Model for Mapping the Cortex,” IEEE Transaction on Medical Image, Vol. 14, No. 1, 65-80, 1995.
[27] B. Leroy, I. Herlin, and L. D. Cohen. “Multiresolution Algorithms for Active Contour Models,” International Conference on Analysis Optimization, Paris, France, 58-65, June 1996.
[28] J. L. Prince and C. Xu. “A New External Force Model for Snakes.” Image and Multidimensional Signal Processing Workshop, 30-31, 1996.
[29] M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis, and Machine Vision, Chapter 4, second edition, PWS Publishing, 1998.
[30] J. Canny, “A Computational Approach to Edge Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-8, No. 6, 1986.
[31] H Freeman, “On the Encoding of Arbitrary Geometric Configuration,” IRE Transactions on Electronic Computers, Vol. EC-10, No. 2, 260-268, 1961.
[32] R. C. Gonzalez and R. E. Woods, Digital Image Processing, Chapter 8 , Addison-Wesley Publishing Company, 1992.
[33] L. D. Stefano and A. Bugareli, “A Simple and Efficient Connected Components Labeling Algorithm,” IEEE Proc. of 10th International Conference on Image Analysis and Processing, 322-327, 1999.
[34] P. V. C. Hough, “ A Method and Means for Recognizing Complex Patterns,” US Patent , 3,069,654, 1962.
[35] Y. Chen and T. Huang, “Optimal Radial Contour Tracking by Dynamic Programming,” Proc. of IEEE ICIP, 2001.