Ochotona curzoniae image segmentation based on the improved LBF model

被引：0
|
作者：
Zhang A. [1 ]
Hu S. [1 ]
Chen H. [1 ,2 ]
机构：
[1] Department of Information and Engineering, Lanzhou University of Technology, Lanzhou
[2] Department of Computer and Communication, Lanzhou University of Technology, Lanzhou
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2016年 / 44卷 / 02期
关键词：
Active contour curve; Image gradient; Image segmentation; Level set; Local binary fitting (LBF) model; Ochotona curzoniae;
D O I：
10.13245/j.hust.160216
中图分类号：
学科分类号：
摘要：
Ochotona curzoniae images possess the characteristics of complex background, low contrast, intensity inhomogeneity and much noise. The improved local binary fitting (LBF) model combined with image gradient information was proposed. As the local binary fitting model has a problem of falling into local minimums easily during the process of evolution, the improved model could avoid falling into the local optimum by bringing in the global image gradient information and creating new energy function. The global gradient energy can lead the active contour curve to the boundaries of target quickly, so it can reduce iteration numbers of the algorithm and improve the segmentation accuracy. The experimental results show that the proposed method can not only improve segmentation accuracy and reduce iteration numbers but also has a positive effect on background suppression and contour location. © 2016, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
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页码：75 / 80
页数：5
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