在图像识别部分，采用了经典的BP神经网络对疵点类型进行分类，同时与改进的SVM分类方法进行比较。

In the image recognition section, classical BP neural network is used to classify the type of defects while we compare with the improved classification method of SVM.

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对于织物疵点的识别分类，本文设计了一个三层BP神经网络，经试验验证对六类织物图像的正确识别率可达95.83%。

For the part of identification of fabric defects, a three layer BP neural network is designed. After testing, six classes fabric image can be correctly identified by the rate of 95.83%.

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帘子布疵点自动检测分为三个部分来完成，分别是图像的预处理、图像分割以及疵点的识别分类。

It is included three parts, namely, image preprocessing, image segmentation and identification classification of the defects.

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