A novel defect detection and identification method in optical inspection

Optical inspection techniques have been widely used in industry as they are non-destructive. Since defect patterns are rooted from the manufacturing processes in semiconductor industry, efficient and effective defect detection and pattern recognition algorithms are in great demand to find out closely related causes. Modifying the manufacturing processes can eliminate defects, and thus to improve the yield. Defect patterns such as rings, semicircles, scratches, and clusters are the most common defects in the semiconductor industry. Conventional methods cannot identify two scale-variant or shift-variant or rotation-variant defect patterns, which in fact belong to the same failure causes. To address these problems, a new approach is proposed in this paper to detect these defect patterns in noisy images. First, a novel scheme is developed to simulate datasets of these 4 patterns for classifiers' training and testing. Second, for real optical images, a series of image processing operations have been applied in the detection stage of our method. In the identification stage, defects are resized and then identified by the trained support vector machine. Adaptive resonance theory network 1 is also implemented for comparisons. Classification results of both simulated data and real noisy raw data show the effectiveness of our method.

Reporting usability defects: limitations of open source defect repositories and suggestions for improvement

Capturing good quality defect reports is critical for ensuring quick resolution of defects. While a range of studies into defect reporting exists, to date, very few focused on usability defect reporting issues can be found. To better understand issues specific to usability defect reporting, we carried out a survey of 56 contributors to the Mozilla and Google Chromium software projects spanning both usability defect reporters and developers. We discovered a range of limitations and key issues in current usability defect reporting tools and approaches identified as important by reporters and developers. In addition, we highlight opportunities to improve defect-reporting tools based on these open source communities' needs.