A Method Based on the Morphology of Lead-Free Solder Powder Adhesive Particle Segmentation

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Abstract:

Three kinds of lead-free soldering tin powder particles produced by means of ultrasonic vibration atomization were studied in this paper. For tin powder particles had higher edge angle and more irregular shape which were the two most key elements that may influence the quality of soldering paste, aspect ratio and fractal dimension of those particles were treated as the facts that could reflect the morphology of soldering tin powder particles. Geometrical projected images of those particles were acquired by optical microscope and image computing were processed by morphologic method. Since particles adhesion phenomenon often occurred in actual image processing of soldering tin powder particles, Roberts operator was used for edge detection and in the meantime, Erosion method and Dilation method in morphological operation were applied to segment those adhesive particles. It was shown that the morphologic method proposed in this paper could be applied to segment those images of adhesive particles.

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Periodical:

Advanced Materials Research (Volumes 690-693)

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2681-2685

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May 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Dj.M. Maric, P.F. Meier and S.K. Estreicher: Mater. Sci. Forum Vol. 83-87 (1992), p.119 LIU Bao-quan. Reviews of the development of soldering tin powder production technology[J], CHINA METAL BULLETIN, 2005, 23: 23~24

Google Scholar

[2] ZHAO Rong-chun, CHI Yao-bin, ZHU Chong-guang. Development of Image Segmentation[J], CHINESE JOURNAL OF STEREOLOGY AND IMAGE ANALYSIS, 1998, 3(2): 121~128.

Google Scholar

[3] ZHOU Ying-li, ZENG Li-bo, LIU Jun-tang et al. A Method for Automatic Colony Counting Based on Image Processing and Its Realization[J], Journal of Data Acquisition & Processing, 2003, 18(4):460~464.

Google Scholar

[4] LIU Sheng-hao, ZENG Li-bo, LIU Bing et al. Separating Algorithm for Overlapping Granule Images[J], Computer Engineering,2002, 28(2): 198~200.

Google Scholar

[5] ZHU Zhi-gang, LIN Xue, SHI Ding-ji. Digital Image Processing[M]. Beijing: Publishing House of Electronics Industry, 1998.

Google Scholar

[6] LUO Jun-hui, FENG Ping, HALITANG·A et al. The Application of MATLAB7.0 in Image Processing[M]. Beijing: China Machine Press, 2005.

Google Scholar