Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (31): 202-205.DOI: 10.3778/j.issn.1002-8331.2010.31.056

• 图形、图像、模式识别 • Previous Articles     Next Articles

Road extraction in remote sensing images based on region growing and GVF-Snake

GU Dan-dan,WANG Xi-li   

  1. School of Computer Science,Shaanxi Normal University,Xi’an 710062,China
  • Received:2009-03-17 Revised:2009-05-21 Online:2010-11-01 Published:2010-11-01
  • Contact: GU Dan-dan



  1. 陕西师范大学 计算机科学学院,西安 710062
  • 通讯作者: 顾丹丹

Abstract: Based on the gray characteristic distribution of the objective to be segmented,an adaptive region growing algorithm is proposed,which can estimate the parameters of homogeneity criterion automatically.And the region growing algorithm with the GVF(Gradient Vector Flow)-snake model is employed to extract roads from high-resolution remote sensing images.In the method,the adaptive region growing algorithm is firstly applied to the preliminary road segmentation,and then mathematical morphology is utilized to eliminate disturbances inside and get the outline of the road in the grown image.Finally,it uses the outline as the initial contour of the GVF-snake model,and applies the model to tracking the road,achieving the final result of the road extraction.Experimental results show that the method is efficient and practical for extracting roads from high-resolution remote sensing images,and has a certain adaptive ability.

Key words: adaptive region growing, GVF-snake model, high-resolution remote sensing images, road extraction

摘要: 基于待分割目标的灰度特征分布,提出了一种能自适应地改变生长准则参数的区域生长方法。将该自适应区域生长算法与GVF-Snake模型相结合用于高分辨率遥感影像道路提取,即用自适应区域生长方法提取出大致的道路区域,对生长出的道路图,利用数学形态学进行内部腐蚀并获得道路区域轮廓线,以该轮廓线作为GVF-Snake模型的初始轮廓,利用GVF-Snake模型进行道路跟踪,得到最终的道路提取结果。实验结果表明该方法能有效地提取高分辨率遥感影像中的道路目标,具有一定的实用性和鲁棒性。

关键词: 自适应区域生长, GVF-Snake模型, 高分辨率遥感影像, 道路提取

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