An expert egg grading system based on machine vision and artificial intelligence techniques

Abstract The main purpose of this research was design and development of an intelligent system based on combined fuzzy logic and machine vision techniques for grading of egg using parameters such as defects and size of eggs. The detected defects were internal blood spots, cracks and breakages of eggshell. The Hue-Saturation-Value (HSV) color space was found useful in obtaining visual features during Image Processing (IP) stage. The fuzzy inference system (FIS) was designed based on triangular and trapezoidal membership functions, fuzzy rules with logical operator of AND inference system of Mamdani and method of center average for defuzzifier. The evaluation results of IP algorithms showed that use of IP technique has good performance for defects and size detection. The Correct Classification rate (CCR) was 95% for size detection, 94.5% for crack detection and 98% for breakage detection. The overall accuracy FIS model in grading of the eggs was 95.4.

[1]  Mahmoud Omid,et al.  Design of an expert system for sorting pistachio nuts through decision tree and fuzzy logic classifier , 2011, Expert Syst. Appl..

[2]  Yankun Peng,et al.  A machine vision system for identification of micro-crack in egg shell , 2012 .

[3]  R. W. McClendon,et al.  Color Computer Vision and Artificial Neural Networks for the Detection of Defects in Poultry Eggs , 1998, Artificial Intelligence Review.

[4]  Jun Wang,et al.  Eggshell crack detection by dynamic frequency analysis , 2005 .

[5]  Domingo Guinea,et al.  Eggshell defects detection based on color processing , 2000, Electronic Imaging.

[6]  Mahmoud Omid,et al.  Grading and Quality Inspection of Defected Eggs Using Machine Vision , 2010 .

[7]  Alasdair McAndrew,et al.  Introduction to digital image processing with Matlab , 2004 .

[8]  Mirko Navara,et al.  Fuzzy controllers with conditionally firing rules , 2002, IEEE Trans. Fuzzy Syst..

[9]  Eakasit Sritham,et al.  Detecting Eggshell Cracks by Acoustic Impulse Response and Artificial Neural Networks , 2003 .

[10]  Raif Bayir,et al.  Determination of modulus of rupture and modulus of elasticity on flakeboard with fuzzy logic classifier , 2009 .

[11]  M B Çelik,et al.  Fault detection in internal combustion engines using fuzzy logic , 2007 .

[12]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[13]  Mahmoud Omid,et al.  An intelligent system for sorting pistachio nut varieties , 2009, Expert Syst. Appl..

[14]  B De Ketelaere,et al.  Dirt detection on brown eggs by means of color computer vision. , 2005, Poultry science.

[15]  H.-K. Cho,et al.  DETECTION OF SURFACE CRACKS IN SHELL EGGS BY ACOUSTIC IMPULSE METHOD , 2000 .

[16]  Kang Tu,et al.  Eggshell crack detection based on computer vision and acoustic response by means of back-propagation artificial neural network , 2011 .