Automated threshold detection for object segmentation in colour image

Object segmentation from single background colour image is important for motion analysis, object tracking, trajectory identification, and human gait analysis. It is a challenging job to extract an object from single background colour image because of the variations of colours and light intensity. Mo...

Full description

Bibliographic Details
Main Authors:	Akhtaruzzaman, Md., Shafie, Amir Akramin, Khan, Md. Raisuddin
Format:	Article
Language:	English English
Published:	Asian Research Publishing Network (ARPN) 2016
Subjects:	TA Engineering (General). Civil engineering (General) TA349 Mechanics of engineering. Applied mechanics
Online Access:	http://irep.iium.edu.my/54857/ http://irep.iium.edu.my/54857/ http://irep.iium.edu.my/54857/1/54857_Automated%20threshold%20detection.pdf http://irep.iium.edu.my/54857/2/54857_Automated%20threshold%20detection_SCOPUS.pdf

id	iium-54857
recordtype	eprints
spelling	iium-548572017-04-18T04:19:39Z http://irep.iium.edu.my/54857/ Automated threshold detection for object segmentation in colour image Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin TA Engineering (General). Civil engineering (General) TA349 Mechanics of engineering. Applied mechanics Object segmentation from single background colour image is important for motion analysis, object tracking, trajectory identification, and human gait analysis. It is a challenging job to extract an object from single background colour image because of the variations of colours and light intensity. Most common solution of the task is the uses of threshold strategy based on trial and error method. As the method is not automated, it is time consuming and sometimes a single threshold value does not work for a series of image frames of video data. In solving this issue, this paper presents an Automated Threshold Detection Algorithm, H(•). The algorithm is applied in segmenting human lower limbs from a series of image frames of human walking. The procedure starts with selection of optimal RGB channel. Then H(•) algorithm is applied for automated threshold detection to convert the image frames into grayscale image. In the next stage, Line Fill (LF) algorithm is applied for smoothing the edges of object and finally background is subtracted to extract the targeted object. Results of the applied procedure show that the algorithm is viable to extract object from single background color image and can be used in human gait analysis. © 2006-2016 Asian Research Publishing Network (ARPN). Asian Research Publishing Network (ARPN) 2016-03 Article PeerReviewed application/pdf en http://irep.iium.edu.my/54857/1/54857_Automated%20threshold%20detection.pdf application/pdf en http://irep.iium.edu.my/54857/2/54857_Automated%20threshold%20detection_SCOPUS.pdf Akhtaruzzaman, Md. and Shafie, Amir Akramin and Khan, Md. Raisuddin (2016) Automated threshold detection for object segmentation in colour image. ARPN Journal of Engineering and Applied Sciences, 11 (6). pp. 4100-4104. ISSN 1819-6608 http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0316_3928.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TA Engineering (General). Civil engineering (General) TA349 Mechanics of engineering. Applied mechanics
spellingShingle	TA Engineering (General). Civil engineering (General) TA349 Mechanics of engineering. Applied mechanics Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin Automated threshold detection for object segmentation in colour image
description	Object segmentation from single background colour image is important for motion analysis, object tracking, trajectory identification, and human gait analysis. It is a challenging job to extract an object from single background colour image because of the variations of colours and light intensity. Most common solution of the task is the uses of threshold strategy based on trial and error method. As the method is not automated, it is time consuming and sometimes a single threshold value does not work for a series of image frames of video data. In solving this issue, this paper presents an Automated Threshold Detection Algorithm, H(•). The algorithm is applied in segmenting human lower limbs from a series of image frames of human walking. The procedure starts with selection of optimal RGB channel. Then H(•) algorithm is applied for automated threshold detection to convert the image frames into grayscale image. In the next stage, Line Fill (LF) algorithm is applied for smoothing the edges of object and finally background is subtracted to extract the targeted object. Results of the applied procedure show that the algorithm is viable to extract object from single background color image and can be used in human gait analysis. © 2006-2016 Asian Research Publishing Network (ARPN).
format	Article
author	Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin
author_facet	Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin
author_sort	Akhtaruzzaman, Md.
title	Automated threshold detection for object segmentation in colour image
title_short	Automated threshold detection for object segmentation in colour image
title_full	Automated threshold detection for object segmentation in colour image
title_fullStr	Automated threshold detection for object segmentation in colour image
title_full_unstemmed	Automated threshold detection for object segmentation in colour image
title_sort	automated threshold detection for object segmentation in colour image
publisher	Asian Research Publishing Network (ARPN)
publishDate	2016
url	http://irep.iium.edu.my/54857/ http://irep.iium.edu.my/54857/ http://irep.iium.edu.my/54857/1/54857_Automated%20threshold%20detection.pdf http://irep.iium.edu.my/54857/2/54857_Automated%20threshold%20detection_SCOPUS.pdf
first_indexed	2023-09-18T21:17:33Z
last_indexed	2023-09-18T21:17:33Z
_version_	1777411664278192128

Automated threshold detection for object segmentation in colour image

Similar Items