计算机应用 ›› 2016, Vol. 36 ›› Issue (2): 526-530.DOI: 10.11772/j.issn.1001-9081.2016.02.0526

• 虚拟现实与数字媒体 • 上一篇    下一篇

基于水平集的手指静脉图像分割

王保生, 陈宇飞, 赵卫东, 周强强   

  1. 同济大学 CAD研究中心, 上海 201804
  • 收稿日期:2015-06-29 修回日期:2015-09-16 出版日期:2016-02-10 发布日期:2016-02-03
  • 通讯作者: 陈宇飞(1982-),女,吉林长春人,讲师,博士,主要研究方向:计算机视觉、图像处理。
  • 作者简介:王保生(1990-),男,江苏连云港人,硕士研究生,主要研究方向:计算机视觉、图像处理;赵卫东(1965-),男,山东青岛人,研究员,博士,主要研究方向:计算机视觉、图像处理;周强强(1980-),男,江西吉安人,博士研究生,主要研究方向:计算机视觉。
  • 基金资助:
    国家自然科学基金资助项目(61103070);同济大学青年优秀人才培养行动计划项目(2013KJ008);中央高校基本科研业务费专项。

Finger-vein image segmentation based on level set

WANG Baosheng, CHEN Yufei, ZHAO Weidong, ZHOU Qiangqiang   

  1. CAD Research Center, Tongji University, Shanghai 201804, China
  • Received:2015-06-29 Revised:2015-09-16 Online:2016-02-10 Published:2016-02-03

摘要: 针对手指静脉图像中存在的弱边缘、灰度不均匀以及低对比度等现象,提出一种结合偶对称Gabor滤波与水平集思想的分割算法,并应用于手指静脉图像的分割。首先,使用偶对称Gabor滤波算法,对手指静脉图像从8个不同的方向分别进行滤波运算;然后,根据8个方向上的滤波结果进行图像重建,得到目标与背景灰度对比度显著提高的图像;最后,应用结合局部与全局信息的水平集方法对手指静脉图像进行分割。将所提算法与Li等水平集算法(LI C, HUANG R, DING Z, et al. A variational level set approach to segmentation and bias correction of images with intensity inhomogeneity. MICCAI'08: Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II. Berlin: Springer, 2008: 1083-1091)、Legendre水平集(L2S)算法相比,所提算法在分割精度评价标准面积差异(AD)百分比上分别降低了1.116%、0.370%,相对差异度(RDD)分别降低了1.661%、1.379%。实验结果表明,与传统只考虑局部信息或全局信息的水平集图像分割算法相比,所提算法能取得更高的分割精度。

关键词: 灰度不均匀, 低对比度, Gabor滤波, 水平集, 图像分割

Abstract: To deal with weak edge, intensity inhomogeneity and low contrast that may appear in finger-vein images, a new segmentation algorithm based on even-symmetric Gabor filter and level set method was proposed. Firstly, the even-symmetric Gabor filter was used to filter the finger-vein image through 8 different orientations; secondly, finger-vein image based on the 8 filtered results was reconstructed to obtain the high quality image with significantly improved gray contrast between target and background; finally, the level set algorithm combining local features and global features was applied to segment finger-vein image. Compared with the level set algorithm proposed by Li, et al. (LI C, HUANG R, DING Z, et al. A variational level set approach to segmentation and bias correction of images with intensity inhomogeneity. MICCAI'08: Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II. Berlin: Springer, 2008: 1083-1091), and Legendre Level Set (L2S) algorithm, the percentage of Area Difference (AD) of the proposed algorithm decreased by 1.116% and 0.370% respectively, and the Relative Difference Degree (RDD) reduced by 1.661% and 1.379% respectively. The experimental results show that the proposed algorithm can achieve better results compared with traditional level set image segmentation algorithms that only consider local information or global information.

Key words: intensity inhomogeneity, low contrast, Gabor filter, level set, image segmentation

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