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

•Design and implementation egg grading expert system by fuzzy logic and machine vision techniques.•The HSV color space was found useful in obtaining visual features during image processing.•The detected defects were internal blood spots, cracks and breakages of eggshell.•The overall accuracy FIS model in grading of the eggs was 95.4.•Through the developed algorithms, the breakage algorithm had the highest accuracy. 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.