基于改进滤波器与小波的印花织物边缘提取

Edge extraction of printed fabric images based on improved filter and wavelet

对部分印花织物图像中存在的丰富纹理信息和混合噪声影响后续印花织物图案提取等深层次处理问题进行研究,提出一种基于改进滤波器与小波模极大值法的印花织物图像边缘提取算法。利用皮尔逊相关系数改进阿尔法均值滤波器,运用连分式逼近思想确定权值;利用自适应权值公式确定权值来改进中值滤波器;利用图像信息熵自适应增大小波模极大值的梯度幅值,根据梯度图像改进二维Otsu算法求取最优分割阈值。实验结果表明,该算法预处理后的图像得到了较好的去噪效果,提高了印花图案边缘提取质量,有利于后期更深层次处理。

The problems of the rich texture information and mixed noise in some printed fabric images,affecting the deep proces-sing of subsequent printed fabric pattern extraction,were studied.An edge extraction algorithm for printed fabric images based on improved filters and wavelet modulus maxima was proposed.Pearson correlation coefficient was used to improve the alpha mean filter,and the continuous approximation was employed to determine the weight.Adaptive weight formula was applied to determine the weight to improve the median filter.Image information entropy was used to adaptively increase the wavelet mode maximum value of the gradient magnitude,and based on the gradient image,the two-dimensional Otsu algorithm was improved to obtain the optimal segmentation threshold.Experimental results show that the pre-processed image has better denoising effects,improves the quality of edge extraction of the printed pattern,and is conductive to deeper processing in the later stage.