Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/146430
Title: Defocus-based image segmentation
Authors: Swain Cassandra
Chen Tsuhan 
Issue Date: 1995
Publisher: IEEE, Piscataway
Citation: Swain Cassandra, Chen Tsuhan (1995). Defocus-based image segmentation. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings 4 : 2403-2406. ScholarBank@NUS Repository.
Abstract: Foreground and background features are focused (or (defocused) differently in an image because corresponding objects are at different depths in the scene. This paper presents a novel approach for segmenting foreground and background in video images based on feature defocus. A modified defocus measurement that distinguishes between high-contrast defocused edges and low-contrast focused edges is presented. Defocus-based segmentation is desirable because defocus techniques are computationally simple. Results indicate that the foreground is easily segmented from moving background. This approach, coupled with motion detection, can segment complex scenes containing both moving background and stationary foreground.
Source Title: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/146430
ISSN: 07367791
Appears in Collections:Staff Publications

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