Enhancement of Background Subtraction Techniques Using a Second Derivative in Gradient Direction Filter. (11th November 2013)

• Record Type: Journal Article
• Authors: Abdul Rahman, Farah Yasmin; Hussain, Aini; Wan Zaki, Wan Mimi Diyana; Badioze Zaman, Halimah; Md Tahir, Nooritawati
• Other Names: Asari Vijayan K. Academic Editor.
• Is Part Of: Journal of electrical and computer engineering. Volume 2013(2013)
• Publication Date: 2013-11-11
• Subjects: Computer engineering -- Periodicals; Electrical engineering -- Periodicals; 621.3905
• DOI: 10.1155/2013/598708
• Languages: English
• ISSNs: 2090-0147

Abstract

Abstract : A new approach was proposed to improve traditional background subtraction (BGS) techniques by integrating a gradient-based edge detector called a second derivative in gradient direction (SDGD) filter with the BGS output. The four fundamental BGS techniques, namely, frame difference (FD), approximate median (AM), running average (RA), and running Gaussian average (RGA), showed imperfect foreground pixels generated specifically at the boundary. The pixel intensity was lesser than the preset threshold value, and the blob size was smaller. The SDGD filter was introduced to enhance edge detection upon the completion of each basic BGS technique as well as to complement the missing pixels. The results proved that fusing the SDGD filter with each elementary BGS increased segmentation performance and suited postrecording video applications. Evidently, the analysis using F -score and average accuracy percentage proved this, and, as such, it can be concluded that this new hybrid BGS technique improved upon existing techniques.