摘要
为了进一步提高现有二值图像欧拉数算法的效率,根据图论中的欧拉定理,提出了一种基于图论的二值图像八邻接欧拉数算法,通过计算与给定图像对应图形中的结点、边和基本面的数量来计算图像的欧拉数。在噪声图像和各种自然图像上的实验结果表明:该算法在大多数情况下都要优于其他现有的欧拉数算法。
This paper presents a graph-theory-based algorithm for computing the 8-neighborhood Euler number in a binary image.Based on the Euler theorem in the graph theory,the Euler number of a given binary image is calculated according to the numbers of nodes,edges and basic squares in the graph corresponding to the image.Experimental results on various kinds of images demonstrate that in most cases the algorithm is more efficient than other conventional Euler number computing algorithms.
作者
姚斌
何立风
康世英
赵晓
巢宇燕
YAO Bin HE Li-feng KANG Shi-ying ZHAO Xiao CHAO Yu-yan(College of Electrical and Information Engineering, Shaanxi Univ. of Science and Technology, Xi＇an 710021, China Faculty of Information Science and Technology, Aichi Prefectural Univ., Aichi 480-1198, Japan School of Information Engineering, Xianyang Normal Univ., Xianyang 712000, China Faculty of Environment, Information and Business, Nagoya Sangyo Univ., Aichi 488-8711, Japan)
出处
《海军工程大学学报》
CAS
北大核心
2016年第5期36-40,共5页
Journal of Naval University of Engineering
基金
国家自然科学基金资助项目(61471227)
陕西省教育厅科研计划资助项目(16JK1099)
关键词
欧拉数
八邻接
模式识别
图像分析与理解
机器视觉
Euler number
8-neighborhood
pattern recognition
image analysis and understanding
machine vision
