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A pattern defect inspection method by parallel grayscale image comparison without precise image alignment

机译:一种模式缺陷检测方法,通过并行灰度图像比较而无需精确图像对齐

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For automatic visual inspection of patterns on printed wiring boards and/or patterned wafers, this paper presents a new defect detection method for grayscale images without precise image alignment. Most of the conventional visual inspection algorithms based on grayscale reference comparison require precise image alignment with precision of subpixel or within +1 pixel; however, it is difficult to succeed the precise image alignment in every image. While a defect inspection method without precise image alignment has been previously proposed for binary images, the expansion to grayscale images we discuss is indispensable for detecting more minute defects. We propose dynamic tolerance control based on grayscale morphology to reduce false defects on pattern edges, and use gray dilation operation so that a weakness of the original method for binary images, an inability to detect the absence of minute patterns, is overcome. Theoretical analysis and experimental results show that the proposed method is capable of detecting subpixel-sized defects, and has practical detection performance.
机译:对于印刷线路板上的图案和/或图案化晶片上的图案的自动目视检查,本文介绍了无需精确图像对齐的灰度图像的新缺陷检测方法。基于灰度参考比较的大多数传统的视觉检查算法需要与子像素的精度或+1像素内的精确图像对齐;然而,难以在每个图像中成功进行精确的图像对齐。虽然先前已经提出了没有精确的图像对准的缺陷检查方法,但是对于二进制图像,我们讨论的灰度图像的扩展是不可或缺的,用于检测更多分钟缺陷。我们提出了基于灰度形态的动态公差控制,以减少图案边缘上的假缺陷,并使用灰度扩张操作,使得二进制图像的原始方法的弱点,无法检测到没有微小模式的缺陷。理论分析和实验结果表明,该方法能够检测亚像素尺寸缺陷,具有实际检测性能。

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