| 摘要: |
| 几何活动轮廓(GAC)模型广泛应用于计算机视觉和图像分析领域,特别是用于定位目标边界.然而,基于GAC模型的图像分割有演化时间长和边界泄漏两个缺点.一方面,停止速度场在同质区域一般不够平滑,这导致活动轮廓不能快速演化到希望的目标边界;另一方面,停止速度场在目标边界上不为0,导致活动轮廓不能停止于目标边界,活动轮廓继续演化进入目标边界内(边界泄漏).针对这两个问题,提出了一种对停止速度场进行各向异性扩散的方法.它基于提出的各向异性扩散模型.然后把各向异性扩散后的停止速度场应用于GAC模型进行图像分割.实验结 |
| 关键词: 图像分割 边界泄漏 活动轮廓模型 停止速度场 各向异性扩散 |
| DOI： |
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| Anisotropic Diffusion of Halting Speed Fields in Geometric Active Contour Model |
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HE Chuan-Jiang,TANG Li-Ming
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| Abstract: |
| Geometrical active contours (GAC) are used extensively in computer vision and image analysis, particularly to locate object boundaries. However, GAC-based segmentations have the drawbacks of long evolving time and boundary leaking. Because halting speed fields (HSF) in GAC models are typically not smooth enough in homogenous region, they are not able to make the active contour quickly move towards the desired object boundaries. On the other hand, the HSF don’t really vanish along the object boundaries, thus the curve propagating can not stop on the object boundaries and continuously move into the object boundaries (boundary leaking). In this paper, an anisotropic diffusion model is therefore presented and then applied to the HSF in GAC model. This GAC-based segmentation with the diffused HSF can overcome the two drawbacks above. Experimental results on a synthetic image and two real world images show the improvements in terms of reducing both the segmentation time and boundary leaking, in comparison of GAC model with the original HSF. |
| Key words: image segmentation boundary leaking active contour model halting speed field anisotropic diffusion |
