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Pixel-level image fusion technique for multi-camera car-body painting defect images

机译:多摄像机车身绘画缺陷图像的像素级图像融合技术

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In automated visual inspection of car-body painting defects, the information quality of defect image is difficult to acquire because of light properties, interference and diffraction. The research, with experimental setup imitating automotive painting production line, acquires some of one light source images taken by 24.2 million pixels digital camera. All images are fused by two pixel-by-pixel fusion methods. Maximum fusion method concerns every pixel in which the pixel, with maximum intensity, is selected. Wavelet fusion method, we merge the two images at decomposition level 1, using db2, taking the maximum for approximation and the maximum for detail. The resulted fusion images of both methods are able to provide some painting defects, such as dust, sagging and peel-off, with useful information of shapes and dimensions.
机译:在自动视觉检查车身涂料缺陷时,由于光特性,干扰和衍射,缺陷图像的信息质量难以获取。该研究与模仿汽车涂料生产线的实验设置,获取由2420万像素数码相机拍摄的一个光源图像。所有图像均由两个像素 - 像素融合方法融合。最大融合方法涉及选择每个像素,其中选择具有最大强度的像素。小波融合方法,我们使用DB2合并分解级别1的两个图像,从而达到最大近似和最大详细信息。所得到的两种方法的融合图像都能够提供一些涂料缺陷,例如灰尘,下垂和剥离,具有形状和尺寸的有用信息。

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