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 Academic Research Journal of Agricultural Science and Research
 

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Academic Research Journal of Agricultural Science and Research 

Vol. 3(9), pp. 258-266. September, 2015.

ISSN: 2360-7874 

 DOI: 10.14662/ARJASR2015.050

 

Full Length Research

Computer Vision System Coupled with an Artificial Neural Network to Quality Evaluation of Rainbow Trout Eggs

 

Ghasem Bahrami1, Sajad Kiani2* and Hossein Rezai 3

 

1MSc Graduated Student of Mechanics of Agricultural Machinery, Faculty of Agriculture, Shiraz University, Fars, Iran.

E-mail: Bahrami.teach@gmail.com.

2 Ph.D Candidate of Biosystems Engineering Dep. Tarbiat Modares University, Tehran, Iran.

*Corresponding authors; e-mails: kiani.sajad@gmail.com.

3Coach of Mechanics of Agricultural Machinery, Faculty of Agriculture, University of Malayer, Ilam, Iran.

E-mail: h.rezaei@malayeru.ac.ir.

 

Accepted 27 July 2015

Abstract

 

Rainbow trout in most of the proliferation and breeding sites of cold-water fishes has been propagated and inbred. One of the proliferation steps of this type of fishes is the separating fertile and living fish eggs from the infertile or dead ones and counting them for sale. In spite of various apparatuses and methods of proliferation, the recognition of fertile from dead fish eggs is essential. In this study the ability of machine vision system coupled with soft computing methods such as Artificial Neural Networks (ANN) was examined to quality assessment of fish eggs. In this regard, the captured images were transferred to the LAB color domain, because this domain is less affected by the camera and lighting conditions then several color and textural features were extracted from the images of rainbow trout fish eggs. Finally extracted features were introduced to ANN as an input layer. As a conclusion results showed that with an optimum adjustment of ANN, the alive and dead fish eggs were classified with 99% accuracy. The outcome of this investigation can be used in the fish egg quality assessment.

Keywords: Fish eggs, Image Processing, Texture Analysis, Color Analysis, Artificial Neural Network


 

How to cite this article: Bahrami G, Kiani S, Rezai H (2015). Computer Vision System Coupled with an Artificial Neural Network to Quality Evaluation of Rainbow Trout Eggs. Acad. Res. J. Agri. Sci. Res. 3(9): 258-266.

 

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Current Issue: September 2015

 

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