基于二维自适应异小波基小波变换的规则纹理缺陷检测

2D Wavelet Transform with Different Adaptive Wavelet Bases for Regular Texture Defect Inspection

许多纹理具有规则的重复出现的纹理单元，如纺织纤维结构。为了处理有缺陷的纹理图象，提出了一种利用不同自适应小波基与纹理模式匹配的二维小波变换的新方法。与Ｄａｕｂｅｃｈｉｅｓ的小波基不同，其行和列采用不同的自适应正交小波基，且用遗传算法得到。实验结果表明该方法能确定纹理缺陷的位置。

There are many textures such as woven fabrics having repeating textron. In order to handle the textural characteristics of images with defects, this paper proposes a new method based on two dimensional wavelet transform. In the method, a new concept of different adaptive wavelet bases is used to match the texture pattern. The 2D wavelet transform has two different adaptive orthonormal wavelet bases for rows and columns which differ from Daubechies wavelet bases. The orthonormal wavelet bases for rows and columns are generated by genetic algorithm. The experimental result demonstrates the ability of the different adaptive wavelet bases to characterize the texture and locate the defects in the texture.