A Machine Vision System for Detecting Fertile Eggs in the Incubation Industry

被引:46
作者
Hashemzadeh, Mahdi [1 ]
Farajzadeh, Nacer [1 ]
机构
[1] Azarbaijan Shahid Madani Univ, Fac Informat Technol & Comp Engn, Tabriz, Iran
关键词
Machine Vision; Image Processing; Egg; Fertility Detection; Incubation Industry; Auto-Candling; IDENTIFICATION;
D O I
10.1080/18756891.2016.1237185
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the important factors in increasing the productivity of the incubation industry is to be sure that the eggs placed in the incubators are fertile. In this research, a fertility detection machine vision system is developed and evaluated. To this end, a mechatronic machine is fabricated for acquiring accurate digital images of eggs without harming them. An appropriate and cheap light source is also introduced for illuminating the eggs, which potentially enables a CCD camera to obtain good quality and informative images from inner side of the eggs. Finally, a robust machine vision algorithm is developed to process the captured images and distinguish fertile eggs from infertile ones. In order to evaluate the system, a large egg image dataset is provided using 240 incubated eggs (including 190 fertile and 50 infertile eggs). The fertility detection accuracy of the system on the provided dataset reaches 47.13% at day 1 of incubation, 81.41% at day 2, 93.08% at day 3, 97.73% at day 4, and 98.25% at day 5. Comparisons with existing approaches show that the proposed method achieves a superior performance. The obtained results indicate that the proposed system is highly reliable and applicable in the incubation industry.
引用
收藏
页码:850 / 862
页数:13
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