ass日本风韵熟妇pics男人扒开女人屁屁桶到爽|扒开胸露出奶头亲吻视频|邻居少妇的诱惑|人人妻在线播放|日日摸夜夜摸狠狠摸婷婷|制服 丝袜 人妻|激情熟妇中文字幕|看黄色欧美特一级|日本av人妻系列|高潮对白av,丰满岳妇乱熟妇之荡,日本丰满熟妇乱又伦,日韩欧美一区二区三区在线

In order to improve the accuracy and reliability of defect detection for packaging cans production lines, an inner surface inspection system with a single camera was studied. By using morphological region extraction algorithms the inspection region of interest image can be obtained from the whole inner image. For defect feature detection an approach based on multivariate image analysis (MIA) was proposed. To cancel the effect of seam regions in the inner images, a method of images fusion was implemented to form the ring-like good sample image without seam region. By stacking both the ring-like good sample images and the test image, the multivariate test images were constructed with their overlapping part. By using MIA technique with principal component analysis (PCA), the principal component scores of the multivariate test images were obtained. As the feature space for defect detection the Q statistic image was derived from the residuals which were left after the extraction of the first PC and noise. The surface defects can be effectively detected using an appropriate threshold. The experimental results show that the proposed inspection system has less sensitivity to the inhomogeneous of illumination, and has more robustness and reliability with pseudo reject rate reducing to 2%.