Corner defect detection based on dot product in ceramic tile images

F. S. Najafabadi, H. Pourghassem
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引用次数: 17

Abstract

One of the important problems in ceramic tile industry is tiles' quality classification with automatic systems by applying machine instead of human. Tiles' quality can be divided into color analysis, dimension verification, and surface defect detection. It's very difficult for human to control all of them, because of harsh industrial environment with noise, extreme temperature and humidity. In this paper, we present a method for visual inspection of ceramic tile corners. We use a method based on image processing techniques and dot product vectors if angle was more than 92 degree or less than 89 degree. Our ceramic is a defective tile. Our algorithm is evaluated on a set of images which has been taken of a Flaw master system in a tile factory and has 12.5% error in both normal and defective tile. The obtained results show efficiency our approach in corner defect detection.
基于点积的瓷砖图像角点缺陷检测
瓷砖行业面临的一个重要问题是用机器代替人工对瓷砖进行自动分类。瓷砖的质量可分为颜色分析、尺寸验证和表面缺陷检测。由于恶劣的工业环境,噪音,极端的温度和湿度,人类很难控制所有这些。本文提出了一种瓷砖边角的目视检测方法。当角度大于92度或小于89度时,我们使用基于图像处理技术和点积向量的方法。我们的瓷砖有缺陷。我们的算法在一组瓦厂缺陷控制系统的图像上进行了评估,在正常和有缺陷的瓦片上都有12.5%的误差。实验结果表明,该方法在边角缺陷检测中是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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