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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
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Asian Research Publishing Network (ARPN)
2016
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| Online Access: | 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 |
| _version_ | 1848784479417532416 |
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| author | Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin |
| author_facet | Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin |
| author_sort | Akhtaruzzaman, Md. |
| building | IIUM Repository |
| collection | Online Access |
| 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). |
| first_indexed | 2025-11-14T16:37:54Z |
| format | Article |
| id | iium-54857 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T16:37:54Z |
| publishDate | 2016 |
| publisher | Asian Research Publishing Network (ARPN) |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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 |
| 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 |
| title | 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_short | Automated threshold detection for object segmentation in colour image |
| title_sort | automated threshold detection for object segmentation in colour image |
| topic | TA Engineering (General). Civil engineering (General) TA349 Mechanics of engineering. Applied mechanics |
| 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 |