[1]彭智东,宣士斌.融合最小生成树和四叉树的图割图像分割方法[J].计算机技术与发展,2018,28(12):102-105.[doi:10．3969/j． issn．1673－629X．2018．12．022]
　PENG Zhidong,XUAN Shibin.Image Segmentation Method Based on Graph Cut Combining Minimum Spanning Tree and Quadtree[J].,2018,28(12):102-105.[doi:10．3969/j． issn．1673－629X．2018．12．022]
点击复制

融合最小生成树和四叉树的图割图像分割方法()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年12期
页码:
102-105
栏目:
智能、算法、系统工程
出版日期:
2018-12-10

文章信息/Info

Title:
Image Segmentation Method Based on Graph Cut Combining Minimum Spanning Tree and Quadtree
文章编号:
1673－629X(2018)12－0102－04
作者:
彭智东; 宣士斌
广西民族大学 信息科学与工程学院，广西 南宁 530006
Author(s):
PENG Zhi－dong; XUAN Shi－bin
School of Information Science and Engineering，Guangxi University for Nationalities，Nanning 530006，China
关键词:
图割; 最小生成树; 四叉树; 最大流/最小割
Keywords:
graph cut; minimum spanning tree; Quadtree; maximum flow /minimum cut
分类号:
TP301
DOI:
10．3969/j． issn．1673－629X．2018．12．022
摘要:
图像分割是图像处理中最关键的步骤，基于图割的图像分割方法近年来备受关注。针对传统图割图像分割方法没有充分考虑相邻相近像素点可能属于不同类的情况，提出了一种结合最小生成树的图割方法。该方法重新构造了能量函数，在能量函数的构造中考虑了原本两个相邻的节点在最小生成树中可能不相邻的情况，对于这种不相邻的情况，重新确定了图中边的权值计算方法，使图的构造更加准确，从而提高了算法的分割精度。但提高算法精度的同时势必会增加算法的复杂度，为降低算法的复杂度，在提出算法中引入了四叉树方法对图像进行预处理，从而减少图中节点的数量。实验结果表明，该方法相比已有的图割方法在分割的精确度和效率上有较大的提高，具有更好的效果。
Abstract:
Image segmentation is the key step in image processing． The image segmentation method based on graph cut has paid much at- tention in recent years． In view of the fact that the traditional image segmentation method does not fully consider the adjacent pixels may belong to different classes，we propose a new image segmentation method combined with minimum spanning tree，which reconstructs the energy function． In the construction of the energy function，the case that two adjacent nodes might not be adjacent in the minimum span- ning tree is considered． For this case，we determine the weight calculation method of the edges in the graph again，which makes the con- struction of the graph more accurate and improves the segmentation accuracy of the algorithm． However，the improvement of algorithm precision is bound to increase the complexity． For this，the quadtree method is introduced to preprocess the image，so as to reduce the number of nodes in the graph． The experiment shows that compared with the existing graph cutting method，the proposed method can greatly improve the precision and efficiency of segmentation with a better effect．

相似文献/References:

[1]唐启涛 陶滔 伍海波.基于最小生成树的LEACH路由算法研究[J].计算机技术与发展,2009,(04):109.
　TANG Qi-tao,TAO Tao,WU Hai-bo.Study of Minimum Spanning Tree Routing Algorithm in LEACH[J].,2009,(12):109.
[2]尹松 周永权 李陶深.基于稀疏差异度的聚类方法在信息分类中的应用[J].计算机技术与发展,2006,(01):117.
　YIN Song,ZHOU Yong-quan,LI Tao-shen.Research of Sparse Feature Difference-Based Clustering Method Applied to Information Classifying[J].,2006,(12):117.
[3]龙占超 蔡超.一种新的指纹细化算法[J].计算机技术与发展,2007,(03):147.
　LONG Zhan-chao,CAI Chao.A New Fingerprint Thinning Algorithm[J].,2007,(12):147.
[4]黄永丽 朱会东 徐华.基于层次性断层数据的三维重构技术[J].计算机技术与发展,2006,(08):60.
　HUANG Yong-li,ZHU Hui-dong,XU Hua.Technology of 3D Reconstruction Based on Layering Cross - Sections Data[J].,2006,(12):60.
[5]孙宪丽 王敏 李颖.求解TSP问题的一种启发式算法[J].计算机技术与发展,2010,(10):70.
　SUN Xian-li,WANG Min,LI Ying.A Heuristic Algorithm to Solve Travelling Salesman Problem[J].,2010,(12):70.
[6]赵林[],朱桂斌[],玉强[],等. 基于最小生成树的规则图像碎片复原算法[J].计算机技术与发展,2016,26(06):69.
　ZHAO Lin[],ZHU Gui-bin[],WEN Yu-qiang[],et al. A Restoration Algorithm for Square Image Pieces Based on MST[J].,2016,26(12):69.
[7]袁恒东.基于标签传递图割的图像分割算法[J].计算机技术与发展,2017,27(12):35.[doi:10.3969/ j. issn.1673-629X.2017.12.008]
　YUAN Heng-dong.An Image Segmentation Algorithm Based on Label Propagation Graph Cut[J].,2017,27(12):35.[doi:10.3969/ j. issn.1673-629X.2017.12.008]
[8]辛壮,万良,李均涛.改进的聚类算法在网络异常行为检测中的应用[J].计算机技术与发展,2019,29(03):111.[doi:10.3969/ j. issn.1673-629X.2019.03.024]
　XIN Zhuang,WAN Liang,LI Jun-tao.Application of Improved Clustering Algorithm in Network Abnormal Behavior Detection[J].,2019,29(12):111.[doi:10.3969/ j. issn.1673-629X.2019.03.024]
[9]王 诚,高兴东.基于最小生成树的密度聚类算法研究[J].计算机技术与发展,2022,32(02):45.[doi:10. 3969 / j. issn. 1673-629X. 2022. 02. 007]
　WANG Cheng,GAO Xing-dong.Research on Density Clustering Algorithm Based on MST[J].,2022,32(12):45.[doi:10. 3969 / j. issn. 1673-629X. 2022. 02. 007]
[10]陈丹冉,王 健.基于图割和局部算子的图子集选取[J].计算机技术与发展,2023,33(06):1.[doi:10. 3969 / j. issn. 1673-629X. 2023. 06. 001]
　CHEN Dan-ran,WANG Jian.Graph Subset Selection via Graph Cut and Localization Operators[J].,2023,33(12):1.[doi:10. 3969 / j. issn. 1673-629X. 2023. 06. 001]

更新日期/Last Update: 2018-12-10