Automated design of the field-of-view, illumination, and image pre-processing parameters of an image recognition system

Yibing Chen, T. Ogata, T. Ueyama, Toshiyuki Takada, J. Ota
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引用次数: 4

Abstract

Machine vision is playing an increasingly important role in the industrial field, and the automated design of image recognition systems has been the subject of intense research. In this study, we proposed a system that is capable of automatically designing the field-of-view of an image recognition system, based on the relationship between the camera and the target objects, the illumination conditions, and the image preprocessing parameters. We reformulated the design problem as an optimization problem, and used a multi-start nearest neighbor search method to solve it. Two evaluation experiments were conducted, with different distances between the target objects. The results demonstrated that the system was able to choose an appropriate field-of-view, illumination conditions, and image pre-processing parameters, taking account of the distance between target objects and the required accuracy of recognition.
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图像识别系统的视场、照明和图像预处理参数的自动设计
机器视觉在工业领域发挥着越来越重要的作用,图像识别系统的自动化设计一直是人们研究的热点。在本研究中,我们提出了一种基于相机与目标物体之间的关系、光照条件和图像预处理参数自动设计图像识别系统视场的系统。我们将设计问题重新表述为优化问题,并采用多起点最近邻搜索法求解。在目标物体距离不同的情况下,进行了两次评价实验。结果表明,该系统能够考虑目标物体之间的距离和所需的识别精度,选择合适的视场、光照条件和图像预处理参数。
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