Earticle

초록

영어

Moving shadow detection is a challenging task in computer vision applications, such as surveillance, video conference, visual tracking, object recognition, and many other important applications. In this paper, region-based moving shadow detection using affinity propagation (RMSDAP) is presented, which detects shadows in terms of texture similarity. Firstly, we divide foreground image into no overlapping blocks and extract color features from each block. Secondly, affinity propagation is utilized to cluster foreground blocks adaptively and sub regions are generated after coarse segmentation. Specially, each sub region has the characteristics of regional uniformity. Finally, we extract texture feature from irregular sub regions while calculate texture similarity and normalized correlation coefficient simultaneously for each sub region to classify moving shadows. Extensive experiments demonstrate that RMSDAP is superior to some well-known methods especially pixel-based methods. In particular, our method exhibits much better performance compared with fixed block method, which can maintain the texture consistency in one region adequately.

목차

Abstract
 1. Introduction
 2. The Proposed Method
  2.1. Adaptive Foreground Segmentation
  2.2. Region-based Shadow Detection
 3. Experiments and Comparisons
  3.1. Parameter Selection
  3.2. Quantitative Comparisons
  3.3. Qualitative Comparisons
 4. Conclusions
 Acknowledgements
 References

키워드

저자

• Jiangyan Dai [ School of Computer Engineering, Weifang University, Weifang, China, 261061 ]
• Dianyuan Han [ School of Computer Engineering, Weifang University, Weifang, China, 261061 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605