An improved snake model for building detection from urban aerial images

  • Authors:
  • Jing Peng;Dong Zhang;Yuncai Liu

  • Affiliations:
  • Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai 200030, P.R. China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai 200030, P.R. China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai 200030, P.R. China

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2005

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Abstract

This paper proposes an improved snake model focusing on building detection from gray-level aerial images of high resolution. Based on the radiometric and geometric behaviors of buildings, the traditional snake model is modified in two aspects: the criteria for the selection of initial seeds and the external energy function. Moreover, the post-treatment combining with illumination information reduces the constraints for initial snake model and the interference caused by illumination, sharply lessening the times of iteration. Compared with traditional snake model, this algorithm can converge to the true building contours more quickly and stably from complex environment.