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Proceedings Paper

Hierarchical object-oriented image and video segmentation algorithm based on 2D entropic thresholding
Author(s): Jianping Fan; Gen Fujita; Jun Yu; Koji Miyanohana; Takao Onoye; Nagisa Ishiura; Lide Wu; Isao Shirakawa
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Paper Abstract

In this paper, a novel object-oriented hierarchical image and video segmentation algorithm is proposed based on 2D entropic thresholding, where the local variance contrast is selected for generating the 2D entropic surface because this parameter can indicate the strength of the edge accurately. The extracted object is first represented by a group of (4 X 4) blocks coarsely, then the intra-block edge extraction procedure and the joint spatiotemporal similarity test among neighboring blocks are further performed for determining the meaningful real objects. Experimental results have confirmed that the proposed hierarchical algorithm may be very useful for MPEG-4 applications, such as determining the Video Object Plane Formation automatically and selecting the coding pattern adaptively. A novel fast algorithm is also introduced for reducing the search burden. Moreover, this unsupervised algorithm also makes the automatic image and video segmentation possible.

Paper Details

Date Published: 19 August 1998
PDF: 11 pages
Proc. SPIE 3561, Electronic Imaging and Multimedia Systems II, (19 August 1998); doi: 10.1117/12.319704
Show Author Affiliations
Jianping Fan, Osaka Univ. and Fudan Univ. (United States)
Gen Fujita, Osaka Univ. (Japan)
Jun Yu, Fudan Univ. (China)
Koji Miyanohana, Osaka Univ. (Japan)
Takao Onoye, Osaka Univ. (Japan)
Nagisa Ishiura, Osaka Univ. (Japan)
Lide Wu, Fudan Univ. (China)
Isao Shirakawa, Osaka Univ. (Japan)


Published in SPIE Proceedings Vol. 3561:
Electronic Imaging and Multimedia Systems II
LiWei Zhou; Chung-Sheng Li, Editor(s)

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