基于颜色直方图和LBP-TD算子的木板材节疤缺陷区域检测

提出一种基于颜色和纹理信息的木板材表面节疤缺陷区域检测方法。首先，根据木板材表面图像中正常区域和缺陷区域的颜色差异，通过颜色直方图自动获取缺陷区域的种子点；然后，提出一种纹理扩散算法，它从种子点出发，基于图像局部纹理特征搜索缺陷区域的边缘。此外，改进了局部二进制模式算子，提出一种LBP-TD算子以更好地适应纹理扩散。实验结果表明:针对各种常见的木板材节疤缺陷，当缺陷区域与正常木纹区域的颜色、纹理存在较明显差异时，无论木纹本身是否规则，本文方法都能准确地检测出木板材节疤缺陷的区域；而当缺陷区域与正常木纹区域的颜色、纹理的差异均不明显时，本文方法仍能检测出缺陷区域的大致轮廓。数据对比显示了本文方法的误检率要低于传统的OTSU法。 

Defective region detection for knot of wood based on color histogram and LBP-TD operator.

In this paper, a new method for defective region detection of wood surface knot using color and texture information was proposed. At first, initial pixels were selected automatically from defective regions based on color histogram through the differences between defective regions and normal wood regions. Then a new algorithm called texture diffusion was proposed to search the contours of defective regions from the initial pixels based on local texture information. Besides, in order to suit the process of texture diffusion, a modified LBP operator named LBP-TD operator was also proposed in this new algorithm. For several kinds of wood surface knot defects, the experiments showed that when obvious differences of color and texture information between defective regions and normal wood regions existed, the accurate contours of knot defective regions could be obtained by the proposed method whether the normal wood surface texture was regular or not. When the differences of color and texture information between defective regions and normal wood regions were not obvious, approximate contours of knot defective regions can also be obtained. Besides, the experimental data showed that the error detection rate of the proposed method was lower than that of OTSU.