应用小波域高斯差分滤波的起球疵点客观评价

受织物背景纹理多样性以及起球疵点特点的影响，传统的图像处理算法难以满足起球疵点自动检测和客观评价需要，为此，提出一种基于小波域的高斯差分滤波起球客观等级新方法。首先，对起球疵点图像进行小波多层分解，实现周期性背景纹理信息与起球信息的分离；然后，选择合适的小波分解子图进行高斯差分滤波，消除噪声以及光照不均等缓变的背景信息，提高起球信息的显著度；在此基础上，根据起球特征设定阈值对起球疵点图像进行分割，并提取起球特征；最后，通过人工神经网络进行起球疵点客观等级评价。试验结果表明，本文方法用于起球疵点客观等级评价是可行且有效的，且具有较强的抗干扰能力。

Pilling objective evaluation based Gaussian filtering in wavelet domain

As the effect of the variety of fabric background textures and the feature of pilling defects, conventional algorithm of image processing is hard to satisfy the automatic detection of pilling defects and the objective evaluating demands. A new way of pilling objective evaluation based on the wavelet-domain of difference of Gaussian filter was proposed. First of all, pilling defect image was decomposed into multiple layers by wavelet multi-decomposition to separation periodic background texture and pilling information. Then, the appropriate wavelet decomposition sub-images were chosen to carry out difference of Gaussian filter for eliminating the noise and the background information of slow variation such as uneven illumination, and pilling information was improved significantly; and on this basis, a segmentation threshold was defined to segment these sub-images according to the characteristics of pilling, and the features of pilling form binary image was extracted. Finally, BP artificial neutral network was used to objective evaluation of pilling grade. The test results show that this method can make an objective evaluation for pilling level effectively, and has strong interference resistance.