2020/10/19 by Milind G. Padalkar, Padalkar, Milind G., Carlos Beltrán-González +7
Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Industrial Vision Systems and Defect Detection #Infrastructure Maintenance and Monitoring #Non-Destructive Testing Techniques
paper · pdf · doi:10.48550/arxiv.2010.09557
openalex publication_date 2020/10/19 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
This paper presents a novel setup for automatic visual inspection of cracks\nin ceramic tile as well as studies the effect of various classifiers and\nheight-varying illumination conditions for this task. The intuition behind this\nsetup is that cracks can be better visualized under specific lighting\nconditions than others. Our setup, which is designed for field work with\nconstraints in its maximum dimensions, can acquire images for crack detection\nwith multiple lighting conditions using the illumination sources placed at\nmultiple heights. Crack detection is then performed by classifying patches\nextracted from the acquired images in a sliding window fashion. We study the\neffect of lights placed at various heights by training classifiers both on\ncustomized as well as state-of-the-art architectures and evaluate their\nperformance both at patch-level and image-level, demonstrating the\neffectiveness of our setup. More importantly, ours is the first study that\ndemonstrates how height-varying illumination conditions can affect crack\ndetection with the use of existing state-of-the-art classifiers. We provide an\ninsight about the illumination conditions that can help in improving crack\ndetection in a challenging real-world industrial environment.\n