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FLAW DETECTION USING IMAGE REGISTRATION AND FUSION TECHNIQUES

机译:利用图像配准和融合技术进行弹跳检测

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摘要

The inspection of polished metal contoured surfaces, such as silverware pieces, is much more difficult than for a flat surface, considering the complex curved surface, reflections, and shadows. It is hard to detect flaws when they overlap with shadows and specular reflections, which is typically the case.rnIn this paper, this problem is solved using image registration and image fusion techniques. A continuous-inspection system is developed to take two images sequentially under different lighting conditions when the object is passing under the camera. Shadows and reflections shift, while the flaws do not. From the differences of these two images, flaws can be distinguished from shadows and reflections, and the lost information due to specular reflections can be made up. Fused images without specular reflections were obtained, and a new feature based image registration algorithm is developed to compare these two fused images to detect the surface flaws.
机译:考虑到复杂的曲面,反射和阴影,检查抛光的金属轮廓表面(例如银器碎片)比平坦表面要困难得多。当瑕疵与阴影和镜面反射重叠时,很难检测到这种情况。通常,这种情况是存在的。本文采用图像配准和图像融合技术解决了这一问题。开发了一种连续检查系统,当物体在摄像机下方通过时,可以在不同的照明条件下连续拍摄两个图像。阴影和反射会移动,而瑕疵不会移动。根据这两个图像的差异,可以将缺陷与阴影和反射区分开,并且可以弥补由于镜面反射而造成的信息丢失。获得了没有镜面反射的融合图像,并开发了一种基于特征的图像配准算法,以比较这两个融合图像以检测表面缺陷。

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