【作者】 谢锋；

【导师】 满家巨；

【作者基本信息】 湖南师范大学 ， 计算机软件与理论， 2007， 硕士

【摘要】 图像分割是图像处理、计算机视觉、模式识别中的核心问题，对它们的发展有非常大的影响。目标轮廓提取是图像分割中的重要研究内容，在图像识别与图像分析中占有重要地位，已广泛应用于军事、医学等许多领域，取得了很多有价值的研究成果。Snake模型是由Kass等人首次提出的算法，广泛地应用于计算机视觉及图像处理中的各个领域，如边缘检测、图像分割、运动跟踪等，特别应用于图像中感兴趣目标轮廓的提取。Snake模型引入高层知识，在处理局部间断的边缘时，提取效果比传统轮廓提取方法要好。自Snake模型出现以来，人们对其作了许多改进，提出了许多不同的目标轮廓提取方法，但由于snake模型本身存在许多不足，尤其是全局最小能量的欠稳定性和收敛速度缓慢等问题，使得Snake模型的应用受到一定制约。本文提出了一种基于Snake模型的边缘轮廓提取的改进算法，该算法主要采用对目标轮廓的中心坐标进行跟踪，同时保持原封闭图像的相关特性，并利用轮廓中心坐标和目标轮廓的相互关系，更快更准确地实现对目标轮廓的迭代，从而加快用Snake模型实现轮廓提取的速度。更多还原

【Abstract】 Image segmentation is a central problem of computer vision. Contour extraction is one of the most important aspects of image segmentation, extensively applied in image analysis, and has a great significance in both theoretical research and industrial applications. Snake model, which was first introduced by Kass, has been used extensively in many applications of computer vision and image processing, such as edge detection, image segmentation and motion tracking, particularly to extract object boundaries. With the introduction of high level information, Snake model has more satisfactory effects than what gained by the traditional method when dealing with disconnected edges in the image.Many improvements in Snake model have been made since they were introduced first by Kass, however, there are many Snake model which is inadequate, especially for its less common minimum energy stability and the slow pace of convergence, which limited on the application. The improvement algorithm of Snake model based on the brink contour extractions, is used to tracking the center coordinates of target contour, while maintaining the original closed images related characteristics by using relationship between the center coordinates and outline the contour of the objectives. In this way, the rate of contour extraction is greatly accelerated.更多还原