Abstract: The industrial image often exists uneven illumination interference, so a local threshold segmentation based on grayscale wave for uneven illumination image is proposed. It extracts image grayscale wave curve in the horizontal and vertical direction, and iteratively searches for larger scale peaks point and troughs point of each curve to meet a given wave amplitude threshold; then, between each pair of alternating peaks or troughs to calculate floating threshold is used to designate the target and background pixels attribution; it takes the intersection of threshold image in two directions to obtain the final segmented image. Experimental results demonstrate that segmentation results and real-time of this method have significantly improved, compared with 2-D Otsu method, 2-D Tsallis entropy method, Niblack method and several algorithms.

Key words: image segmentation, local threshold segmentation, grayscale wave, floating threshold

摘要： 针对工业图像经常存在不均匀光照的干扰，提出一种光照不均匀图像的灰度波动局部阈值分割算法。从水平及垂直方向上提取图像的灰度波动曲线，并迭代搜索每条曲线上满足给定波动幅度阈值的较大尺度波峰点和波谷点；在每对交替波峰点或波谷点之间求取浮动阈值来划定目标和背景像素的归属；对两个方向上取得的阈值图像进行相交操作得到最终分割图像。实验结果表明，与二维Otsu法、二维Tsallis熵法、Niblack法等几种算法相比，该算法的分割效果及实时性都具有明显的提升。

关键词: 图像分割, 局部阈值分割, 灰度波动, 浮动阈值