弱边缘电荷耦合器件羊毛图像二值化算法

为解决弱边缘图像二值化产生羊毛几何尺寸失真问题，通过对基于灰度和梯度指数的边缘细化算法研究，结合经典的全局阈值法和局部阈值法，提出了一种电荷耦合器件（CCD）羊毛图像自动二值化算法。该算法将sobel算子和斜坡边缘模型引入现有边缘细化算法中，既增加寻找边缘点环节又改进灰度调整因子，达到提高处理效率和避免人为干预的目的；在分析最大类间方差法和Bernsen法的基础上，结合全局和局部阈值处理各个子图像，从而强化边缘细节，降低失真度。实验结果表明，与传统方法相比，该算法对于弱边缘图像二值化具有良好的性能。

Binarization algorithm for CCD wool images with weak contour

In order to solve the distortion of wool geometric dimension,resulting from image binarization with weak contour,an automatic binarization algorithm for Charge-Coupled Device(CCD) wool image was proposed with reference to a ramp-width-reduction approach based on intensity and gradient indices,using a classical global threshold method and a local one.In that algorithm,edge-pixel-seeking step was added and gray-adjusting factor was improved,with sobel operator and ramp edge model introduced,to increase processing efficiency and avoid human intervention.Besides,every sub image was processed by the mixed global and local threshold based on the analysis of Otsu’s and Bernsen’s methods to intensify edge details and decrease distortion.Compared with the traditional ways,the experimental results show that the new algorithm has good performance in automatic binarization with weak contour.