TY  - JOUR
T1  - Automatic Detection of Eggshell Defects Based on Machine Vision
AU - , H.R. Pourreza AU - , A.H. Naebi AU - , S. Fazeli AU - , B. Taghizade 
JO  - Journal of Animal and Veterinary Advances
VL  - 7
IS  - 10
SP  - 1200
EP  - 1203
PY  - 2008
DA  - 2001/08/19
SN  - 1680-5593
DO  - javaa.2008.1200.1203
UR  - https://makhillpublications.co/view-article.php?doi=javaa.2008.1200.1203
KW  - Machine vision
KW  -image processing
KW  -histogram
KW  -high pass filter
KW  -sorting
KW  -poultry industry
KW  -egg
AB  - Grading defected eggs is one of the important needs of poultry industry, because of sanitary and also economic reasons. Separating cracked and dirty eggs in primary steps of packing is an inevitable necessity to protect other eggs and mechanical parts from contamination. This study presents an automatic method based on colored image processing for recognition of eggshell defects. This method is based on recognition of discontinuities in image caused by eggshell defects. This algorithm uses a high pass filter to determine discontinuities. Finally, the deficiency of an egg is considered after applying an adaptive threshold to the filtered picture. The result of this method is more reliable than the methods given before.
ER  -