欢迎访问《图学学报》 分享到:

图学学报

• 视觉与图像 • 上一篇    下一篇

融合区域和测地线的活动轮廓模型与图割相结合的自然图像分割

  

  • 出版日期:2015-10-30 发布日期:2015-11-05

Combining Region-Based Model with Geodesic Active Contour for Nature Image Segmentation Using Graph Cut Optimization

  • Online:2015-10-30 Published:2015-11-05

摘要: 针对活动轮廓模型利用水平集函数演化来分割图像时,只能分割灰度均匀的图像
问题以及容易陷入能量泛函局部极小值的缺点,提出一种新的图像分割模型。模型将区域中的
局部和全局信息融合的活动轮廓模型与边界模型相结合,然后利用图切割进行优化。实验表明,
该方法对初始曲线不敏感,能分割灰度不均的自然图像,避免陷入局部极小,并能有效提高图
像分割的速度和精度。

关键词: 图像分割, 活动轮廓, 水平集方法, 图割

Abstract: As the active contour model segments images using level set formulation, such formulation
results in very slow algorithms that get easily stuck in local solutions and only segment image with
intensity homogeneity. In this paper, a new model combining region-based with geodesic active
contours is proposed for image segmentation. The new energy functional can be iteratively minimized
by graph cut algorithms with high computational efficiency compared with the level set framework.
Experiment results show that the proposed model can effectively and efficiently segment images with
intensity inhomogeneity. The method is less sensitive to the location of initial contour and can also
avoid local minima solutions.

Key words: image segmentation, active contours, level set method, graph cut