一种复杂图像目标的分割与识别

An Approach to Complex Target Segmentation and Recognition

研究受光照等因素影响表面灰度随机变化的空中图像目标的分割与识别．提出了改进的多阈值八邻域像素比较边线检测算法，对得到的边缘像素进行填充，并在跟踪过程中消除轮廓上的短校及图像干扰，最后采用快速多边形近似算法，用多边形顶角及目标形状因子作为特征对目标进行识别．解决了此类复杂图像目标分割困难的问题，取得了较好的分割效果，识别率高．验证了利用图像像素与其邻域像素的灰度比较检测边缘、分割目标以及利用多边形近似算法识别目标的有效性和鲁棒性．

To investigate the segmentation and recognition of complex target whose gray has stochastic distribution, a new edge detection method, which used the gray levels of the pixel to compare with those of its eight neighbors, was presented to segment the target. After filling in the edge pixels and eliminating image disturbances, a fast polygon approximation algorithm was implemented to get the polygon of the target with fixed angles for recognition. The approach solved the difficulty of segmening such a complex image and got a good result of segmentation and recognition. It is effective and robust to detect the edge and recognize the target with the approach presented above.