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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Main Authors: Ke Xiao, Guandong Gao, Li Shou
Format: Article
Language:English
Published: IFSA Publishing, S.L. 2014-04-01
Series:Sensors & Transducers
Subjects:
Online Access:http://www.sensorsportal.com/HTML/DIGEST/april_2014/Vol_169/P_2004.pdf
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spelling 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.
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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