Quick light mixing of multiple color sources for image acquisition using pattern search

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• 作者：HyungTae Kim ; KyeongYong Cho ; SeungTaek Kim…
• 关键词：Color mixer ; Optimal illumination ; Image sharpness ; Chromaticity ; Pattern search ; Machine vision
• 刊名：International Journal of Precision Engineering and Manufacturing
• 出版年：2015
• 出版时间：October 2015
• 年：2015
• 卷：16
• 期：11
• 页码：2353-2358
• 全文大小：583 KB
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  13.Kim, H. T., Kim, S. T., and Kim, J. S., 鈥淢ixed-Color Illumination and Quick Optimum Search for Machine Vision,鈥?International Journal of Optomechatronics, Vol. 7, No. 3, pp. 207鈥?21, 2013.CrossRef
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• 作者单位：HyungTae Kim (1)
  KyeongYong Cho (2)
  SeungTaek Kim (1)
  Jongseok Kim (1)
  KyungChan Jin (1)
  
  1. Manufacturing System R&D Group, Korea Institute of Industrial Technology, 89, Yangdaegiro-gil, Ipjang-myeon, Seobuk-gu, Cheonan-si, Chungcheongnam-do, 31056, South Korea
  2. CELAB, B135, Mobile Habour, MunJi Campus, KAIST, 291, Daehak-ro, Yuseong-gu, Daejeon, 34141, South Korea
  
• 刊物类别：Engineering
• 刊物主题：Industrial and Production Engineering
  Materials Science
  
• 出版者：Korean Society for Precision Engineering, in co-publication with Springer Verlag GmbH
• ISSN：2005-4602

文摘

Illumination is one of the inspection conditions in industrial machine vision and highly related with image quality. Single light source is commonly used and adjusted to acquire fine images during setup. The image acquisition is described by nonlinear and complex equations, and a color mixing source additionally requires multi-dimensional formulation. So, this paper applied a direct, nondifferential, multi-dimensional search method for optimal illumination conditions using pattern search. The pattern search is one of the optimum methods and was modified for this optimal illumination and multiple color sources in machine vision. The pattern search in this paper was discussed about how to organize a probe network for this optimal illumination of image acquisition. The pattern search was composed of probe network of multiple dimensions, probing sharpness, translation, shrinkage, and terminal condition. The proposed method can maximize image sharpness and minimize iterative adjustment in the test results of an RGB mixer, which was more effective than the case of equal step search. The pattern search algorithm for this optimal illumination provides automatic and quick lighting control in image inspection process. The proposed method decreased the iterations under 1% of conventional search, and it is very efficient on time and energy saving. Keywords Color mixer Optimal illumination Image sharpness Chromaticity Pattern search Machine vision