红外与激光工程, 2001, 30 (1): 12, 网络出版: 2006-04-28
基于四叉树结构的图像分割技术
Image segmentation based on the structure of quadtree
摘要
基于四叉树结构的图像分割方法是区域增长技术和人工智能技术的结合，它的分割速度比区域增长方法快得多，在分割结束时，算法同时得到图像目标大小、目标灰度、目标个数、目标边缘等结果。对多目标图像分割有更好的适应性。文章最后用激光烧孔图像、细胞图像和海上舰船图像进行了实验，说明算法有很好的适应性。
Abstract
A new method of imagesegmentation is developed. The method is evolved by region growing and artificialintelligence combination. The performance of the method is better than region growing, asits calculation speed is faster and program more simple, moreover it can give moreinformation, such as size, gray level, edge and number of object. An experiment is made onlaser image, cell image and warship image at last. Experimental results have shown thatour method is effective to the different object images.
参考文献
[1] 王润生. 图像理解［M］. 长沙：国防科技大学出版社，1995.
[2] . Region Growing: A New Approach[J]. IEEE Transactions on image processing, 1998, 7(7): 1079-1084.
[3] . Integrating region growing and edge detection[J]. IEEE Trans. Pattern Anal. Machine Intell, 1990, 12: 225-233.
[4] . A new algorithm for image segmentation based on region growing and edge detection[J]. Proc. Int. Symp. Circuits and Systems, 1991, 1: 516-519.
王广君, 田金文, 柳健. 基于四叉树结构的图像分割技术[J]. 红外与激光工程, 2001, 30(1): 12. 王广君, 田金文, 柳健. Image segmentation based on the structure of quadtree[J]. Infrared and Laser Engineering, 2001, 30(1): 12.
PDF全文
