Moving objects segmentation and extraction based on motion blur features. (May 2018)

• Record Type: Journal Article
• Authors: Zhou, Luoyu; Zhang, Zhengbing
• Is Part Of: Computers & electrical engineering. Volume 68(2018)
• Page Start: 490
• Page End: 498
• Publication Date: 2018-05
• Subjects: Image segmentation -- Motion blur features -- Prior information -- Energy function -- Morphological method -- Contourlet transform; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.05.003
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: In order to restore the spatially-varying blur images whose background is sharp, it is necessary that the moving objects are segmented and extracted from the blur images. So this paper proposes a novel segmentation and extraction method based on motion blur features. Firstly, the blur features are extracted by using contourlet transform and considered as the prior information. Then an energy function is proposed for extracting the moving object from the original images. Moreover, considering that there exists some noise in segmented images, some morphological methods are introduced to remove the noise. The experimental results demonstrate the proposed scheme achieves high-quality segmentation performance and it outperforms the existing methods when used for moving objects segmentation.