带钢表面缺陷检测方法

Strip surface defect detection method

为了检测出生产过程中带钢表面缺陷,提出了一种改进的mallat算法对其表面缺陷的检测方法。在小波分解中,大部分小波滤波器长度大于1,分解出的图像是有限长序列,这样原始的mallat算法就会截取一部分滤波器长度作用于有限长序列来实现小波分解,导致重构后的图像失真。解决这一问题的根本方法是构造正交小波基,通过信息熵来确定小波分解层数。对重构后的图像进行二值化,通过形态学分析去除二值图像存在的噪声,得到分割后的缺陷图像。matlab进行仿真结果表明,改进的mallat算法对缺陷图像分割方法是可靠的。

To detect the defect of strip surface while producing, the improved mallat alogrithm is applied to the strip surface defect detection. In WT decomposition, most Of the length of the wavelet filters are longer than 1, but the lenght of decom posed image is limited. So mallat alogrithm intercepts part of lenght of the wavelet filters for image to realize decomposition, which leads to reconstructed image ditorting. Sructing orthonorma[ wavelet basis is basic method to solve this problem. Wavelet decomposition level is decided by image entropy. The reconstruction images are translated into binarization images, the binarized images are obtained and the low-level noises involved in those images are removed by morphological analysis method, thus the segmented defective images are provided. The experimental results by simulation verify the reliability of the method proposed.