Adaptive Multi-Seed Geometric Active Contour Model for River Recognition

摘要：

This paper presents a novel multi-seed vector-valued framework for river recognition based on geometric active contours. There are four core components of this framework: vector-valued scanning algorithm, a geometric active contours model, low resolution segmentation with elevation data and high resolution optimization. The combined algorithm allows for a rapid evolution of the contour and a convergence to its final configuration with a small number of iterations. Compared with the conventional segmentation methods, our approach has the advantages of dealing effectively with complicated satellite images, automatically initializing a number of snakes based on color and texture features, accurately and rapidly identifying the target objects with elevation data.

作者: C.Wang T.R.Wan I.J.Palmer

作者单位: EIMC, School of Informatics, University of Bradford, UK

会议类型: 国际会议

会议名称: 2008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)

会议地点: 镇江

会议语种:英文

页码: 312-316

在线出版日期: 2008-07-07（万方平台首次上网日期，不代表论文的发表时间）