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  • 标题:A Novel Approach for Object Detection in VHR Images
  • 本地全文:下载
  • 作者:Ashwini Kunte ; Siddhesh Shirodker ; Rakesh Menaria
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2013
  • 卷号:6
  • 期号:4
  • 出版社:SERSC
  • 摘要:This paper presents two methods for buildings extraction in Very High Resolution (VHR) remotely sensed multispectral (4 band) images based on supervised and unsupervised segmentation using different image properties. The proposed approach for unsupervised or automatic building detection involves four stages, primarily, filtering to smoothen and enhance the objects present and sharpen the details. Secondly, a binary mask creation over which edge detection is applied. Edge linking is done to preserve information about the object. Lastly region properties like area, perimeter, etc are applied on the prepared mask and buildings are detected. The semi-automated or supervised method uses advanced color based segmentation algorithm to extract the buildings tops. This technique creates a number of masks based on segmentation and uses region properties based on color. Experiments are made on VHR images captured from satellites of commercial companies like Digital Globe and Geo Eye. Results of both methods are compared with respect to various accuracy measures at the end. The results illustrate that supervised algorithm using color property produces more accurate object delineation.
  • 关键词:VHR images; Building Detection; Edge based Segmentation; Color based Segmentation
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