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作者:

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

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EI Scopus

摘要:

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.

关键词:

Behavioral research Extraction Image segmentation Neural networks

作者机构:

  • [ 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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来源 :

年份: 2008

页码: 375-378

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 13

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 2

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