https://scholars.lib.ntu.edu.tw/handle/123456789/118011
Title: | Fast Search Algorithms for Industrial Inspection | Authors: | CHANG, MING-CHING Fuh, Chiou-Shann CHEN, HSIEN-YEI |
Keywords: | Alignment; Computer vision; Defect detection; Digital image processing; Normalized cross-correlation; Similarity measure; Subpixel accuracy; Visual inspection | Issue Date: | 2001 | Journal Volume: | 15 | Journal Issue: | 4 | Start page/Pages: | 675-690 | Source: | International Journal of Pattern Recognition and Artificial Intelligence15 (4): 675-690 | Abstract: | This paper presents an efficient general purpose search algorithm for alignment and an applied procedure for IC print mark quality inspection. The search algorithm is based on normalized cross-correlation and enhances it with a hierarchical resolution pyramid, dynamic programming, and pixel over-sampling to achieve subpixel accuracy on one or more targets. The general purpose search procedure is robust with respect to linear change of image intensity and thus can be applied to general industrial visual inspection. Accuracy, speed, reliability, and repeatability are all critical for the industrial use. After proper optimization, the proposed procedure was tested on the IC inspection platforms in the Mechanical Industry Research Laboratories (MIRL), Industrial Technology Research Institute (ITRI), Taiwan. The proposed method meets all these criteria and has worked well in field tests on various IC products. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-0035360048&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/292179 http://ntur.lib.ntu.edu.tw/bitstream/246246/154678/1/26.pdf |
ISSN: | 02180014 | DOI: | 10.1142/S0218001401001039 |
Appears in Collections: | 資訊工程學系 |
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