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Visual Abnormalities Detecting based on Similarity Matching

机译:基于相似性匹配的视觉异常检测

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摘要

Abnormalities detecting is one important application in the field of image processing and pattern recognition. It can alleviate human workload and improve productivity that employing computer graphic image theory and image processing technology analyzes and matches images in order to detect the abnormal region in image which has broad application prospects. In this paper, we propose a new abnormality detecting method based on similarity matching to address whether either missing or error abnormalities existing in bound books in industrial situation. First of all, we denoise the image by means of digital image processing and transformation, extract the sub rectangular region containing bound books using contour matching and locate the area exactly matching the template image using template matching. After that, we get a binary denoised image to detect the missing abnormality and the error abnormality using shape matching. In addition, we introduce some thresholds to improve the performance. The experiments show that the method we proposed achieve a better or the same performance comparing with the state-of-the-art methods.
机译:异常检测是图像处理和模式识别领域的一个重要应用。它可以缓解人类工作量,提高采用计算机图形图像理论和图像处理技术分析的生产率,并匹配图像以检测具有广泛应用前景的图像中的异常区域。在本文中,我们提出了一种基于相似性匹配的新异常检测方法,以解决工业状况界定书中存在的缺失或误差异常。首先,我们通过数字图像处理和转换来表示图像,使用轮廓匹配提取包含绑定书籍的子矩形区域,并使用模板匹配定位与模板图像完全匹配的区域。之后,我们获得二进制去噪图像以检测使用形状匹配的缺失的异常和错误异常。此外,我们介绍了一些阈值来提高性能。实验表明,我们提出的方法实现了与最先进的方法相比的更好或相同的性能。

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