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Author:

Jing, Zhang (Jing, Zhang.) (Scholars:张菁) | Li, Zhuo (Li, Zhuo.) | Lansun, Shen (Lansun, Shen.)

Indexed by:

EI Scopus

Abstract:

The presented research addressed a novel visual attention model and watershed segmentation based approach of Regions of Interest (ROIs) extraction, which automatically extracts ROIs and copes with the watershed over-segmentation. This approach uses visual attention model to locate salient points, in which the winner point, the most salient point, is selected as the seed point of watershed segmentation. ROIs are extracted by combining salient regions with watershed segmented regions. The focus of attention (FOA) is shifted to measure the importance or interest of the extracted regions. The experimental results show that the proposed method is effective to reduce over-segmentation in auto-extracting ROIs and performs well for different objects. © 2008 IEEE.

Keyword:

Extraction Image segmentation Neural networks Behavioral research

Author Community:

  • [ 1 ] [Jing, Zhang]Signal and Information Processing Lab., Beijing University of Technology, 100 PingLeYuan, Chaoyang District, Beijing, 100124, China
  • [ 2 ] [Li, Zhuo]Signal and Information Processing Lab., Beijing University of Technology, 100 PingLeYuan, Chaoyang District, Beijing, 100124, China
  • [ 3 ] [Lansun, Shen]Signal and Information Processing Lab., Beijing University of Technology, 100 PingLeYuan, Chaoyang District, Beijing, 100124, China

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Source :

Year: 2008

Page: 375-378

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 13

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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