Earticle

초록

영어

This paper presents a non-stationary object detection method by exploring time-varying spatial domain information in full motion video. Initially, the edge maps of difference image between two adjacent frames and current frame is generated via the well-known Canny edge detector. The distance of the edge pixels between the difference image and the current video frame are confined within a small value to determine the initial edge mask for the object in motion. The horizontal and vertical filling followed by morphological opening and closing operator are applied on the initial edge mask to create initial temporal segmentation mask of the moving object. The morphological dilation and corrosion operator are utilized to obtain binary marker image of the foreground and background which are used to modify the multi-scale morphological gradient image of current frame. Finally, the watershed algorithm is performed on the modified gradients to find the non-stationary objects accurately in the spatial domain of motion frames. Processed video results show detection accuracy of 98% and 99% for four different video experimentation test-beds involving fast and slow human motion. In this operation, the proposed technique eliminates the problem of over-segmentation of the watershed algorithm and extracts visually distinct, contextually meaningful non-stationary objects as they randomly appear (or disappear) in video sequences.

목차

Abstract
 1. Introduction
 2. Description of the Overall Approach
 3. Temporal Segmentation
  3.1. Edge Detection of Moving Object
  3.2. Extraction of Moving Object Mask
 4. Spatial Segmentation
  4.1. Multi-Scale Morphological Gradient
  4.2. Marker Extraction
 5. Experimental Results
 6. Conclusions
 References

키워드

저자

• Qingqing Fu [ College of Electronics and Information Engineering, Yangtze University, Jingzhou, Hubei, China ]
• Silin Xu [ College of Meteorology and Oceanography, PLA Univ of Sci.&Tech ]
• Aiping Wu [ College of Electronics and Information Engineering, Yangtze University, Jingzhou, Hubei, China ] Corresponding Author

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