The University of Southampton
University of Southampton Institutional Repository

Robust foreground extraction technique using background subtraction with multiple thresholds

Robust foreground extraction technique using background subtraction with multiple thresholds
Robust foreground extraction technique using background subtraction with multiple thresholds
We propose a robust method to extract silhouettes of foreground objects from color-video sequences. To cope with various changes in the background, we model the background as a Laplace distribution and update it with a selective running average and static pixel observation. All pixels in the input video image are classified into four initial regions using background subtraction with multiple thresholds. Shadow regions are eliminated using color components, and the final foreground silhouette is extracted by smoothing the boundaries of the foreground and eliminating errors inside and outside of the regions. Experimental results show that the proposed algorithm works very well in various background and foreground situations.
Background subtraction, Foreground segmentation, Silhouette extraction, Algorithms, Image coding, Pixels, Video streaming, Feature extraction
0091-3286
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Sakamoto, R.
6cdb329c-4cb0-42d6-b4b0-68b448304398
Kitahara, I.
13b48c1f-8b52-4b65-9f98-e00c2bee22df
Toriyama, T.
060a3980-f003-4b15-b0fb-7e9e99acc471
Kogure, K.
9862d198-bf93-48a3-a954-dd8bce232b8b
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Sakamoto, R.
6cdb329c-4cb0-42d6-b4b0-68b448304398
Kitahara, I.
13b48c1f-8b52-4b65-9f98-e00c2bee22df
Toriyama, T.
060a3980-f003-4b15-b0fb-7e9e99acc471
Kogure, K.
9862d198-bf93-48a3-a954-dd8bce232b8b

Kim, H., Sakamoto, R., Kitahara, I., Toriyama, T. and Kogure, K. (2007) Robust foreground extraction technique using background subtraction with multiple thresholds. Optical Engineering, 46 (9), [097004]. (doi:10.1117/1.2779022).

Record type: Article

Abstract

We propose a robust method to extract silhouettes of foreground objects from color-video sequences. To cope with various changes in the background, we model the background as a Laplace distribution and update it with a selective running average and static pixel observation. All pixels in the input video image are classified into four initial regions using background subtraction with multiple thresholds. Shadow regions are eliminated using color components, and the final foreground silhouette is extracted by smoothing the boundaries of the foreground and eliminating errors inside and outside of the regions. Experimental results show that the proposed algorithm works very well in various background and foreground situations.

This record has no associated files available for download.

More information

Published date: 1 September 2007
Additional Information: Cited By :22 Export Date: 30 April 2020 CODEN: OPEGA
Keywords: Background subtraction, Foreground segmentation, Silhouette extraction, Algorithms, Image coding, Pixels, Video streaming, Feature extraction

Identifiers

Local EPrints ID: 440551
URI: http://eprints.soton.ac.uk/id/eprint/440551
ISSN: 0091-3286
PURE UUID: 56fb34df-97cd-4387-a230-9ab599c9cb5f
ORCID for H. Kim: ORCID iD orcid.org/0000-0003-4907-0491

Catalogue record

Date deposited: 07 May 2020 16:31
Last modified: 17 Mar 2024 04:01

Export record

Altmetrics

Contributors

Author: H. Kim ORCID iD
Author: R. Sakamoto
Author: I. Kitahara
Author: T. Toriyama
Author: K. Kogure

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×