到目前为止,纹理分析技术在许多应用中用于代替人工来检测材料缺陷,这些材料包括地毯、汽车涂料和最常用的纺织品。Dewaele等人[31]使用自的英语翻译

到目前为止,纹理分析技术在许多应用中用于代替人工来检测材料缺陷,这些材

到目前为止,纹理分析技术在许多应用中用于代替人工来检测材料缺陷,这些材料包括地毯、汽车涂料和最常用的纺织品。Dewaele等人[31]使用自适应滤波器实现检测纺织图像中点和线的缺陷。Chetvenikov[32]通过滤波提取纹理特征,然后对其使用一个简单的窗口差异算子检测纹理存在的缺陷边界。Chen和Jain[33]使用结构方法来检测缺陷,首先提取纹理的整个框架,然后通过对其统计存在的异常来检测缺陷。Bodnarova[34]使用Gabor滤波器组来检测纺织品中存在的许多缺陷。
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结果 (英语) 1: [复制]
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So far, texture analysis technology has been used in many applications to replace manual to detect material defects, including carpets, automotive coatings and the most commonly used textiles. Dewaele et al. [31] used adaptive filters to detect defects in points and lines in textile images. Chetvenikov [32] extracts texture features by filtering, and then uses a simple window difference operator to detect the defect boundary of the texture. Chen and Jain [33] used structural methods to detect defects, first extracting the entire frame of the texture, and then detecting defects by statistically analyzing their anomalies. Bodnarova [34] uses Gabor filter bank to detect many defects in textiles.
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结果 (英语) 2:[复制]
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To date, texture analysis techniques have been used in many applications to detect defects in materials, including carpets, automotive coatings and the most commonly used textiles. Dewaele et al. use adaptive filters to detect defects in the midpoint and lines of textile images. Chetvenikov extracts texture features through filtering, and then uses a simple window differential operator to detect defect boundaries in the texture. Chen and Jain use structural methods to detect defects, first extracting the entire frame of the texture, and then detecting defects by statistically present exceptions. Bodnarova uses the Gabor filter set to detect many defects in textiles.
正在翻译中..
结果 (英语) 3:[复制]
复制成功!
So far, texture analysis technology has been used in many applications to replace human to detect material defects, including carpets, automotive coatings and the most commonly used textiles. Dewaele et al. [31] use adaptive filter to detect the defects of midpoint and line in textile image. Chetvenikov [32] extracts texture features by filtering, and then uses a simple window difference operator to detect the defect boundary of texture. Chen and Jain [33] use structural methods to detect defects, first extract the whole framework of texture, and then detect defects by counting the existing exceptions. Bodnarova [34] uses Gabor filter banks to detect many defects in textiles.
正在翻译中..
 
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