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研究生: 余智偉
Yu, Zhi-Wei
論文名稱: 適應性影像強化技術在焊錫缺陷檢驗之應用
Adaptive Image Contrast Enhancement for Defect Detection of Solder Joints
指導教授: 彭明輝
Perng, Ming-Hwei
口試委員: 陳世亮
蔡宏營
彭明輝
學位類別: 碩士
Master
系所名稱: 工學院 - 動力機械工程學系
Department of Power Mechanical Engineering
論文出版年: 2011
畢業學年度: 99
語文別: 中文
論文頁數: 75
中文關鍵詞: 適應性影像強化對比強化
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  • 現今的消費性電子產品以降低生產週期、大量生產和產品品質穩定為目標,同時為了因應電子元件趨向微小化,大量運用了表面黏著技術(SMT),由於此過程中的錫膏材料、刮刀壓力與速度、鋼板開孔形狀等因素,在自動化的生產中產品難免會產生缺陷,若想增加自動檢測的穩健性就必須先將影像做強化處理,本研究針對四方平面無引腳封裝(QFN)底部的導熱片與印刷電路板之間的焊錫空洞缺陷檢驗發展穩健的影像強化法,以利於後續的檢測。
    本研究分成兩個部分:第一部分是分析目前已應用於導熱片空洞缺陷檢測的適應性影像強化法,並提出改良,再以實驗結果驗證此改良確實能增強檢測的穩健性; 第二部分發展兩個更強健的適應性影像強化法,這兩個方法各有其適用條件,本研究將討論實驗結果並給出使用建議。


    摘要.................................................I 致謝................................................II 目錄...............................................III 圖目錄..............................................IV 第一章 簡介.........................................1 1-1問題背景與研究動機................................2 1-2 文獻回顧.........................................5 1-2-1 影像強化技術...................................5 1-2-2 影像分割技術..................................16 1-3 問題定義與研究策略..............................21 第二章 基於局部統計值之適應性影像強化法............24 2-1 既有局部統計值之適應性影像強化法之介紹..........25 2-2 既有局部統計值之適應性影像強化法之優缺點分析....33 2-3局部統計值之適應性影像強化法之改良...............36 2-4 結果與討論......................................37 第三章 背景移除之適應性影像強化法...................45 3-1基於內插之適應性影像強化法.......................45 3-2基於形態學之適應性影像強化法.....................55 第四章 實驗結果與討論...............................59 第五章 結論.........................................71 參考文獻............................................72

    [1] 蔡聰男,「自適應式表面黏著製程品質預測控制系統之發展」,
    博士論文,成功大學製造工程研究所,民國92年。

    [2] 陳洊丞,「電腦斷層影像與表面封裝元件之校正與缺陷檢測」,碩
    士論文,清華大學動力機械工程學系,民國98年。

    [3] 立錡科技,取自http://www.cntronics.com/public/pdfupload/App
    Note QA200501-A Footprint Design and Surface Mount Application
    for QFNDFN Package.pdf,2011。

    [4] R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed.
    Englewood Cliffs, NJ: Prentice-Hall, 2002.

    [5] M. L. Cocklin, A. R. Gourlay, P. H. Jackson, G. Kaye, I. H. Kerr, and
    P. Lams, “Digital processing of chest radiographs,” Image and Vision
    Computing, vol. 1, pp. 67-78, 1983.

    [6] G. A. Johnson, N. Danieley, and C. E. Ravin, “Processing alternatives
    for digital chest imaging,” Radiologic Clinics of North America,
    vol. 23, pp. 335-340, 1985.

    [7] H. D. Cheng and X. J. Shi, “A simple and effective histogram
    equalization approach to image enhancement,” Digital signal
    processing, vol. 14, pp. 158-170, 2004.

    [8] D.J. Ketcham, R. W. Lowe, and J. W. Weber, “Real-time
    enhancement techniques,” Seminar on Image Processing,
    Hughes Aircraft, pp. 1–6, 1976.

    [9] R. A. Hummel, “Image enhancement by histogram transformation,”
    Computer Vision, Graphics and Image Processing, vol. 6,
    pp. 184–195, 1977.

    [10] S. M. Pizer, J. B. Zimmerman, and E. V. Staab, “Adaptive grey level
    assignment in CT scan display,” Journal of computer assisted
    tomography, vol. 8, pp. 300-308, 1984.

    [11] R. H. Sherrier and G. Johnson, “Regionally adaptive histogram
    equalization of the chest,” Medical Imaging, IEEE Transactions on,
    vol. 6, pp. 1-7, 1987.

    [12] S. M. Pizer, E. P. Amburn, J. D. Austin, R. Cromartie,
    A. Geselowitz, T. Greer, B. ter Haar Romeny, J. B. Zimmerman, and
    K. Zuiderveld, “Adaptive histogram equalization and its variations,”
    Computer vision, graphics, and image processing, vol. 39,
    pp. 355-368, 1987.

    [13] A. M. Reza, “Realization of the contrast limited adaptive histogram
    equalization (CLAHE) for real-time image enhancement,” The
    Journal of VLSI Signal Processing, vol. 38, pp. 35-44, 2004.

    [14] J. Y. Kim, L. S. Kim, and S. H. Hwang, “An advanced contrast
    enhancement using partially overlapped sub-block histogram
    equalization,” Circuits and Systems for Video Technology, IEEE
    Transactions on, vol. 11, pp. 475-484, 2001.

    [15] P. G. Tahoces, J. Correa, M. Souto, C. Gonzalez, L. Gomez, and
    J. J. Vidal, “Enhancement of chest and breast radiographs by
    automatic spatial filtering,” Medical Imaging, IEEE Transactions
    on, vol. 10, pp. 330-335, 1991.

    [16] T. Peli and J. S. Lim, “Adaptive filtering for image enhancement,”
    Optical Engineering, vol. 21, pp. 108-112, 1982.

    [17] M. Ishida, P. H. Frank, K. Doi, and J. L. Lehr, “High quality digital
    radiographic images,” Radiographics, vol. 3, pp. 325-338, 1983.

    [18] P. M. Narendra and R. C. Fitch, “Real-time adaptive contrast
    enhancement,” Pattern Analysis and Machine Intelligence, IEEE
    Transactions on, vol. PAMI-3, pp. 655-661, 1981.

    [19] D. H. Ballard and C. M. Brown, Computer Vision. Englewood Cliffs,
    NJ: Prentice-Hall, 1982.

    [20] S. Mukhopadhyay and B. Chanda, “A multiscale morphological
    approach to local contrast enhancement,” Signal Processing, vol. 80,
    pp. 685-696, 2000.

    [21] A. R. Jimenez-Sanchez, J. D. Mendiola-Santibanez, I. R.
    Terol-Villalobos, G. Herrera-Ruiz, D. Vargas-Vazquez,
    J. J. Garcia-Escalante, and A. Lara-Guevara, “Morphological
    background detection and enhancement of images with poor
    lighting,” Image Processing, IEEE Transactions on, vol. 18,
    pp. 613-623, 2009.

    [22] I. R. Terol-Villalobos, “Morphological connected contrast mappings
    based on top-hat criteria: A multiscale contrast approach,” Optical
    Engineering, vol. 43, pp. 1577–1595, 2004.

    [23] Z. Y. Chen, B. R. Abidi, D. L. Page, and M. A. Abidi, “Gray-level
    grouping (glg): An automatic method for optimized image contrast
    enhancement-part II: The variations,” Image Processing, IEEE
    Transactions on, vol. 15, pp. 2303-2314, 2006.

    [24] N. Otsu, “A threshold selection method from gray-level histograms,”
    Automatica, vol. 11, pp. 285-296, 1975.

    [25] J. MacQueen, “Some methods for classification and analysis of
    multivariate observations,” Proceedings of 5-th Berkeley
    Symposium on Mathematical Statistics and Probability, University
    of California Press, 1967, pp. 281-297.

    [26] Z. Yu and C. Bajaj, “A fast and adaptive method for image contrast
    enhancement,” in IEEE International Conference on Image
    Processing, 2004, pp. 1001-1004, vol. 2.

    [27] L. Vincent, “Morphological grayscale reconstruction in image
    analysis: Applications and efficient algorithms,” Image Processing,
    IEEE Transactions on, vol. 2, pp. 176-201, 1993.

    [28] 劉育鑫,「偵測氣泡瑕疵之適應性分割技術」,碩士論文,
    清華大學動力機械工程學系,民國100年。

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