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Rapid Automatic Lighting Control of a Mixed Light Source for Image Acquisition using Derivative Optimum Search Methods

机译:使用衍生优化搜索方法的图像采集的混合光源的快速自动照明控制

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Automatic lighting (auto-lighting) is a function that maximizes the image quality of a vision inspection system by adjusting the light intensity and color.In most inspection systems, a single color light source is used, and an equal step search is employed to determine the maximum image quality. However, when a mixed light source is used, the number of iterations becomes large, and therefore, a rapid search method must be applied to reduce their number. Derivative optimum search methods follow the tangential direction of a function and are usually faster than other methods. In this study, multi-dimensional forms of derivative optimum search methods are applied to obtain the maximum image quality considering a mixed-light source. The auto-lighting algorithms were derived from the steepest descent and conjugate gradient methods, which have N-size inputs of driving voltage and one output of image quality. Experiments in which the proposed algorithm was applied to semiconductor patterns showed that a reduced number of iterations is required to determine the locally maximized image quality.
机译:自动照明(自动照明)是通过调整光强度和颜色来最大化视觉检测系统的图像质量的功能。在大多数检查系统中,使用单个颜色光源,采用等步骤搜索来确定最大图像质量。然而,当使用混合光源时,迭代的数量变大,因此,必须应用快速搜索方法以减少它们的数量。衍生优化搜索方法遵循功能的切向方向,通常比其他方法快。在该研究中,应用多维形式的衍生优化搜索方法来获得考虑混合光源的最大图像质量。自动照明算法源自陡峭的下降和共轭梯度方法,其具有用于驱动电压的n尺寸输入和图像质量的一个输出。将所提出的算法应用于半导体图案的实验表明,需要减少的迭代数量来确定局部最大化的图像质量。

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