Earticle

초록

영어

This paper presents algorithms based on image processing for detecting internal blood spots and eggshell dirt by processing acquired images from eggs under different illuminations. The algorithm can also detect the severity of dirt on eggshell. In order to carry out image processing and extract useful features of captured images of eggs by machine vision we developed an algorithm in HSI color space. The hue histogram was used for blood spots detection, and maximum values of two ends of histogram were selected as criterions of defect detection. Eggshell dirt was detected using connected areas detection technique. The results of experiments showed that accuracy of differentiation of blood spots algorithm was 90.66% of defected eggs and 91.33% of intact eggs and total average of this algorithm was 91%. Accuracy of differentiation of dirt detect algorithm was 86% of clean eggs, 83% of low dirt eggs and 88% of high dirt eggs. Then total average of this algorithm was 85.66%.

목차

Abstract
 1. Introduction
 2. Materials and methods
  2.1. Blood Spots
  2.2. Dirt
 3. Results and Discussion
 4. Conclusions
 References

키워드

저자

• M.H. Dehrouyeh [ PhD Student ]
• M. Omid [ Associated Professor, Department of Agricultural Machinery Engineering ]
• H. Ahmadi [ Faculty of Agriculture Engineering and Technology, School of Agriculture & Natural Resources, University of Tehran, Karaj, Iran. ]
• S.S. Mohtasebi [ Associated Professor, Department of Agricultural Machinery Engineering ]
• M. Jamzad [ Associate Professor, Faculty of Computer Engineering, Sharif University of Technology, Tehran, Iran. ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Science and Technology

• 간기

  월간

• pISSN

  2005-4238

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605