针对特定工业现场环境下成捆棒材端面图象的分割问题,提出了一种基于融合技术的图象分割方案.该方案先分别采用阈值化与基于边界的分割方法对图象进行初始分割,然后将所得数据加以关联,并采用遗传算法加以融合与提取.实验结果表明,该方案在不明显增加计算量的同时,使分割质量有了明显提高.

In view of industrial spot and the particular requirements of the segmentation for the end image when the bar steel were bundled up, a new image segmentation approach is presented. At first. the image is preliminary segmented with threshold method and edge based method, by using the fast 2-D entropic thresholding algorithm and the simple gradient operator respectively. Then the results from the two methods are fused and integrated, the target areas are identified and the adhesions are removed, in which genetic algorithm is implemented. The fusion-based technique is shown to perform very well in terms of robustness to noise and adhesions, and the calculating time is not evidently added. The experimental result shows that the proposed approach is efficient in improving the quality of segmentation and fitting the industrial requirement.