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Automatic Recognition Analysis of Fabric Structure Based on GLCM and BP Neural Network

机译:基于GLCM和BP神经网络的织物结构自动识别分析

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At present, the work to analyze fabric structure still depends on artificial visual measurement, which is easily influenced by personal sight, mood, mental state as well as light condition. With the development of image processing technology and artificial intelligence, automatic analysis on fabric structure as a replacement of manual labor is of great possibility. In this study, features of fabric-image have been extracted by GLCM (Gray Level Co-occurrence Matrix). These features were analyzed by employing a three layer BP neural network. Three kinds of fabric structures such as plain, twill and satin was verified and the accurate recognition rate is very high to 93.45%.
机译:目前,分析织物结构的作品仍然取决于人工视觉测量,这很容易受到个人视力,情绪,精神状态以及轻度条件的影响。随着图像处理技术和人工智能的发展,织物结构的自动分析为替代手工劳动的可能性。在该研究中,通过GLCM(灰度共发生矩阵)提取了织物图像的特征。通过采用三层BP神经网络来分析这些特征。验证了三种织物结构,如普通,斜纹,缎面结构,准确的识别率很高至93.45%。

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