Detecting gallbladders in chicken livers using spectral analysis

Anders Jørgensen; Eigil Mølvig Jensen; Thomas B. Moeslund

doi:10.5244/C.29.MVAB.2

Detecting gallbladders in chicken livers using spectral analysis

Anders Jørgensen, Eigil Mølvig Jensen, Thomas B. Moeslund

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Abstract

This paper presents a method for detecting gallbladders attached to chicken livers using spectral imaging. Gallbladders can contaminate good livers, making them unfit for human consumption. A data set consisting of chicken livers with and without gallbladders, has been captured using 33 wavelengths within the visible spectrum. This work shows how to reduce the high number of wavelengths while maintaining a high accuracy. A classification tree has be trained to evaluate if a gallbladder is present and whether it is suitable for automatic removal, which could increase profits for the processing plants. As a preliminary study this shows good results with a classification accuracy of 91.7%.

Original language	English
Title of host publication	Proceedings of the Machine Vision of Animals and their Behaviour (MVAB)
Editors	T. Amaral, S. Matthews, T. Plötz, S. McKenna, R. Fisher
Number of pages	8
Publisher	British Machine Vision Association
Publication date	10 Sept 2015
DOIs	https://doi.org/10.5244/C.29.MVAB.2
Publication status	Published - 10 Sept 2015
Event	British Machine Vision Conference 2015: Machine Vision of Animals and their Behaviour - Swansea University, Swansea, United Kingdom Duration: 7 Sept 2015 → 10 Sept 2015 Conference number: 26

Conference

Conference	British Machine Vision Conference 2015
Number	26
Location	Swansea University
Country/Territory	United Kingdom
City	Swansea
Period	07/09/2015 → 10/09/2015

Keywords

Chicken
Poultry
Gall
Spectral
hyperspectral imaging
image analysis

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10.5244/C.29.MVAB.2

http://www.bmva.org/bmvc/2015/mvab/papers/paper002/index.html

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@inproceedings{8bf3907b75e34883920949d1f24d1311,

title = "Detecting gallbladders in chicken livers using spectral analysis",

abstract = "This paper presents a method for detecting gallbladders attached to chicken livers using spectral imaging. Gallbladders can contaminate good livers, making them unfit for human consumption. A data set consisting of chicken livers with and without gallbladders, has been captured using 33 wavelengths within the visible spectrum. This work shows how to reduce the high number of wavelengths while maintaining a high accuracy. A classification tree has be trained to evaluate if a gallbladder is present and whether it is suitable for automatic removal, which could increase profits for the processing plants. As a preliminary study this shows good results with a classification accuracy of 91.7%.",

keywords = "Chicken, Poultry, Gall, Spectral, hyperspectral imaging, image analysis",

author = "Anders J{\o}rgensen and {M{\o}lvig Jensen}, Eigil and Moeslund, {Thomas B.}",

year = "2015",

month = sep,

day = "10",

doi = "10.5244/C.29.MVAB.2",

language = "English",

editor = "T. Amaral and S. Matthews and T. Pl{\"o}tz and S. McKenna and R. Fisher",

booktitle = "Proceedings of the Machine Vision of Animals and their Behaviour (MVAB)",

publisher = "British Machine Vision Association",

note = "British Machine Vision Conference 2015 : Machine Vision of Animals and their Behaviour ; Conference date: 07-09-2015 Through 10-09-2015",

}

Jørgensen, A, Mølvig Jensen, E & Moeslund, TB 2015, Detecting gallbladders in chicken livers using spectral analysis. in T Amaral, S Matthews, T Plötz, S McKenna & R Fisher (eds), Proceedings of the Machine Vision of Animals and their Behaviour (MVAB). British Machine Vision Association, British Machine Vision Conference 2015, Swansea, United Kingdom, 07/09/2015. https://doi.org/10.5244/C.29.MVAB.2

Detecting gallbladders in chicken livers using spectral analysis. / Jørgensen, Anders; Mølvig Jensen, Eigil; Moeslund, Thomas B.
Proceedings of the Machine Vision of Animals and their Behaviour (MVAB). ed. / T. Amaral; S. Matthews; T. Plötz; S. McKenna; R. Fisher. British Machine Vision Association, 2015.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Detecting gallbladders in chicken livers using spectral analysis

AU - Jørgensen, Anders

AU - Mølvig Jensen, Eigil

AU - Moeslund, Thomas B.

N1 - Conference code: 26

PY - 2015/9/10

Y1 - 2015/9/10

N2 - This paper presents a method for detecting gallbladders attached to chicken livers using spectral imaging. Gallbladders can contaminate good livers, making them unfit for human consumption. A data set consisting of chicken livers with and without gallbladders, has been captured using 33 wavelengths within the visible spectrum. This work shows how to reduce the high number of wavelengths while maintaining a high accuracy. A classification tree has be trained to evaluate if a gallbladder is present and whether it is suitable for automatic removal, which could increase profits for the processing plants. As a preliminary study this shows good results with a classification accuracy of 91.7%.

AB - This paper presents a method for detecting gallbladders attached to chicken livers using spectral imaging. Gallbladders can contaminate good livers, making them unfit for human consumption. A data set consisting of chicken livers with and without gallbladders, has been captured using 33 wavelengths within the visible spectrum. This work shows how to reduce the high number of wavelengths while maintaining a high accuracy. A classification tree has be trained to evaluate if a gallbladder is present and whether it is suitable for automatic removal, which could increase profits for the processing plants. As a preliminary study this shows good results with a classification accuracy of 91.7%.

KW - Chicken

KW - Poultry

KW - Gall

KW - Spectral

KW - hyperspectral imaging

KW - image analysis

U2 - 10.5244/C.29.MVAB.2

DO - 10.5244/C.29.MVAB.2

M3 - Article in proceeding

BT - Proceedings of the Machine Vision of Animals and their Behaviour (MVAB)

A2 - Amaral, T.

A2 - Matthews, S.

A2 - Plötz, T.

A2 - McKenna, S.

A2 - Fisher, R.

PB - British Machine Vision Association

T2 - British Machine Vision Conference 2015

Y2 - 7 September 2015 through 10 September 2015

ER -

Detecting gallbladders in chicken livers using spectral analysis

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Keywords

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