基于反射的机器视觉光优化设计

Guangming Gao, Xiaojun Wu
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引用次数: 2

摘要

在机器视觉系统中,照明是获取高质量图像的重要因素之一,它可以保证应用的效率和鲁棒性。针对以往基于经验轨迹和误差选择照明系统的惯例,提出了一种基于表面反射特性(如粗糙度、表面反射率指数、方向等)的LED照明系统设计优化模型,以最大限度地提高感兴趣特征与背景之间的对比度。该优化模型适用于广泛的材料。利用该方法可以得到使目标与背景对比度最大的最优参数,如入射角、波长、光强等。通过实验和仿真,我们提出的方案可以获得对比度最大的高质量图像,为机器视觉中优化LED照明系统设计提供了一种有效的方法,可以简化算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Light optimal design for machine vision based on reflection
Illumination is one of the most important elements to capture high quality images in machine vision systems, which can guarantee the efficiency and robustness of the applications. Contrary to the experience based trail and error convention to select a light system, a optimization model for LED illumination system design is proposed based on the surface reflection characteristics, e.g. the roughness, the index of surface reflectivity, direction, etc, to maximize the contrast between the features of interest and the background. The optimization model applies to a wide range of materials. And it can be used to get the optimal parameters which make the contrast between target and background be biggest, such as incidence angle, wavelength and intensity of light. Through experiments and simulations, our proposed scheme can achieve high quality images with biggest contrast, which would be an efficient methodology for optimal LED light system design in machine vision to simplify the algorithm.
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