Sunglass detection method for automation of video surveillance system
Wearing sunglass to hide face from surveillance camera is a common activity in criminal incidences. Therefore, sunglass detection from surveillance video has become a demanding issue in automation of security systems. In this paper we propose an image processing method to detect sunglass from survei...
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| Format: | Conference or Workshop Item |
| Language: | English |
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IOP Publishing Ltd
2018
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| Online Access: | http://umpir.ump.edu.my/id/eprint/21451/ http://umpir.ump.edu.my/id/eprint/21451/ http://umpir.ump.edu.my/id/eprint/21451/1/Sunglass%20detection%20method%20for%20automation%20of%20video%20surveillance%20system.pdf |
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ump-21451 |
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eprints |
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ump-214512020-02-21T07:43:03Z http://umpir.ump.edu.my/id/eprint/21451/ Sunglass detection method for automation of video surveillance system Tasriva, Sikandar Wan Nur Azhani, W. Samsudin Kamarul Hawari, Ghazali Izzeldin, I. Mohd Mohammad Fazle, Rabbi TK Electrical engineering. Electronics Nuclear engineering Wearing sunglass to hide face from surveillance camera is a common activity in criminal incidences. Therefore, sunglass detection from surveillance video has become a demanding issue in automation of security systems. In this paper we propose an image processing method to detect sunglass from surveillance images. Specifically, a unique feature using facial height and width has been employed to identify the covered region of the face. The presence of covered area by sunglass is evaluated using facial height-width ratio. Threshold value of covered area percentage is used to classify the glass wearing face. Two different types of glasses have been considered i.e. eye glass and sunglass. The results of this study demonstrate that the proposed method is able to detect sunglasses in two different illumination conditions such as, room illumination as well as in the presence of sunlight. In addition, due to the multi-level checking in facial region, this method has 100% accuracy of detecting sunglass. However, in an exceptional case where fabric surrounding the face has similar color as skin, the correct detection rate was found 93.33% for eye glass. IOP Publishing Ltd 2018-04 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/21451/1/Sunglass%20detection%20method%20for%20automation%20of%20video%20surveillance%20system.pdf Tasriva, Sikandar and Wan Nur Azhani, W. Samsudin and Kamarul Hawari, Ghazali and Izzeldin, I. Mohd and Mohammad Fazle, Rabbi (2018) Sunglass detection method for automation of video surveillance system. In: International Conference on Innovative Technology, Engineering and Sciences (iCITES 2018), 1-2 March 2018 , Universiti Malaysia Pahang, Pahang, Malaysia. pp. 1-9., 342 (1). ISSN 17578981 http://iopscience.iop.org/article/10.1088/1757-899X/342/1/012040/pdf |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Malaysia Pahang |
| building |
UMP Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
TK Electrical engineering. Electronics Nuclear engineering |
| spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering Tasriva, Sikandar Wan Nur Azhani, W. Samsudin Kamarul Hawari, Ghazali Izzeldin, I. Mohd Mohammad Fazle, Rabbi Sunglass detection method for automation of video surveillance system |
| description |
Wearing sunglass to hide face from surveillance camera is a common activity in criminal incidences. Therefore, sunglass detection from surveillance video has become a demanding issue in automation of security systems. In this paper we propose an image processing method to detect sunglass from surveillance images. Specifically, a unique feature using facial height and width has been employed to identify the covered region of the face. The presence of covered area by sunglass is evaluated using facial height-width ratio. Threshold value of covered area percentage is used to classify the glass wearing face. Two different types of glasses have been considered i.e. eye glass and sunglass. The results of this study demonstrate that the proposed method is able to detect sunglasses in two different illumination conditions such as, room illumination as well as in the presence of sunlight. In addition, due to the multi-level checking in facial region, this method has 100% accuracy of detecting sunglass. However, in an exceptional case where fabric surrounding the face has similar color as skin, the correct detection rate was found 93.33% for eye glass. |
| format |
Conference or Workshop Item |
| author |
Tasriva, Sikandar Wan Nur Azhani, W. Samsudin Kamarul Hawari, Ghazali Izzeldin, I. Mohd Mohammad Fazle, Rabbi |
| author_facet |
Tasriva, Sikandar Wan Nur Azhani, W. Samsudin Kamarul Hawari, Ghazali Izzeldin, I. Mohd Mohammad Fazle, Rabbi |
| author_sort |
Tasriva, Sikandar |
| title |
Sunglass detection method for automation of video surveillance system |
| title_short |
Sunglass detection method for automation of video surveillance system |
| title_full |
Sunglass detection method for automation of video surveillance system |
| title_fullStr |
Sunglass detection method for automation of video surveillance system |
| title_full_unstemmed |
Sunglass detection method for automation of video surveillance system |
| title_sort |
sunglass detection method for automation of video surveillance system |
| publisher |
IOP Publishing Ltd |
| publishDate |
2018 |
| url |
http://umpir.ump.edu.my/id/eprint/21451/ http://umpir.ump.edu.my/id/eprint/21451/ http://umpir.ump.edu.my/id/eprint/21451/1/Sunglass%20detection%20method%20for%20automation%20of%20video%20surveillance%20system.pdf |
| first_indexed |
2023-09-18T22:31:29Z |
| last_indexed |
2023-09-18T22:31:29Z |
| _version_ |
1777416315290517504 |