2015 年 81 巻 12 号 p. 1198-1205
Recently, demand has grown for defect detection processes utilizing machine vision applications. This is especially needful for the abovementioned IC lead frames used in semiconductor manufacture, which require both high quality and miniaturization. In previous work, we proposed a detection method that assumes the variance in the intensity of oriented gradients in images that include defective areas will be larger than that found in acceptable areas. Therefore, there is a tendency to detect defects that has large variance in the local image. However, when conventional image processing methods are used for verifying a defect of deformation in flat parts, it was confirmed that the detection was difficult. Image processing methods using the surface normal direction is proposed in order to detect defect of deformation in flat parts. Since most of these methods use a fixed parameter, when these methods detect for various defects in industrial parts, there is a risk of missing a defect. In this paper, another defect detection method is proposed for detecting various defect sizes and defect types. This method determines appropriate block size based on median value of luminance dispersions calculated on several block sizes. In our experimental results, our proposal method can achieve good performance to detect defects in several sizes.