An Improved Method of Detecting Pork Freshness Based on Computer Vision in On-line System
On the basis of computer vision, this paper studied and developed an on-line detection system for pork freshness, which include the overall design of the system scheme, the hardware design and functions, the software functions and detection algorithm. The systematical hardware is composed of image a...
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doaj-7bfea7fdd4e84c7ba316f06ef35f173c2020-11-24T21:12:29ZengIFSA Publishing, S.L.Sensors & Transducers2306-85151726-54792014-04-0116944248An Improved Method of Detecting Pork Freshness Based on Computer Vision in On-line SystemKe Xiao0Guandong Gao1Li Shou2College of Information Science and Technology, Agricultural University of Hebei 289, Ling Yu Si Road, Baoding 071001, Hebei, China Information and Management Department, The Central Institute for Correctional Police 41, Qi Yi Road, Baoding 071000, Hebei, China Information and Management Department, The Central Institute for Correctional Police 41, Qi Yi Road, Baoding 071000, Hebei, ChinaOn the basis of computer vision, this paper studied and developed an on-line detection system for pork freshness, which include the overall design of the system scheme, the hardware design and functions, the software functions and detection algorithm. The systematical hardware is composed of image acquisition unit, light source unit, control unit, drive transmission device and computer. For the software implementation of the collected images, the processes include three steps as following: 1) Otsu algorithm was applied to remove the disturbance of background and other noises. 2) The fat areas were eliminated according to color difference between pork fat and the muscle. 3) A new Color Region Ratio (CRR) feature extraction method applying color-layering approach was proposed for the identification of pork freshness. The testing of 100 samples have shown that the CRR feature is highly correlated with pork freshness, reaching 88 % detection accuracy, and it is feasible to use CRR feature to detect the pork freshness. http://www.sensorsportal.com/HTML/DIGEST/april_2014/Vol_169/P_2004.pdfPorkFreshness detectionOn-line detection systemColor region ratioHardware software design. |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ke Xiao Guandong Gao Li Shou |
spellingShingle |
Ke Xiao Guandong Gao Li Shou An Improved Method of Detecting Pork Freshness Based on Computer Vision in On-line System Sensors & Transducers Pork Freshness detection On-line detection system Color region ratio Hardware software design. |
author_facet |
Ke Xiao Guandong Gao Li Shou |
author_sort |
Ke Xiao |
title |
An Improved Method of Detecting Pork Freshness Based on Computer Vision in On-line System |
title_short |
An Improved Method of Detecting Pork Freshness Based on Computer Vision in On-line System |
title_full |
An Improved Method of Detecting Pork Freshness Based on Computer Vision in On-line System |
title_fullStr |
An Improved Method of Detecting Pork Freshness Based on Computer Vision in On-line System |
title_full_unstemmed |
An Improved Method of Detecting Pork Freshness Based on Computer Vision in On-line System |
title_sort |
improved method of detecting pork freshness based on computer vision in on-line system |
publisher |
IFSA Publishing, S.L. |
series |
Sensors & Transducers |
issn |
2306-8515 1726-5479 |
publishDate |
2014-04-01 |
description |
On the basis of computer vision, this paper studied and developed an on-line detection system for pork freshness, which include the overall design of the system scheme, the hardware design and functions, the software functions and detection algorithm. The systematical hardware is composed of image acquisition unit, light source unit, control unit, drive transmission device and computer. For the software implementation of the collected images, the processes include three steps as following: 1) Otsu algorithm was applied to remove the disturbance of background and other noises. 2) The fat areas were eliminated according to color difference between pork fat and the muscle. 3) A new Color Region Ratio (CRR) feature extraction method applying color-layering approach was proposed for the identification of pork freshness. The testing of 100 samples have shown that the CRR feature is highly correlated with pork freshness, reaching 88 % detection accuracy, and it is feasible to use CRR feature to detect the pork freshness.
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topic |
Pork Freshness detection On-line detection system Color region ratio Hardware software design. |
url |
http://www.sensorsportal.com/HTML/DIGEST/april_2014/Vol_169/P_2004.pdf |
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