Eggshell defects detection based on color processing

The automatic classification of defective eggs constitutes a fundamental issue of the poultry industry for both economical and sanitary reasons. The early separation of eggs with spots and cracks is a relevant task as the stains can leak while progressing on the conveyor-belts, degrading all the mechanical parts. Present work is focused on the implementation of an artificial vision system for detecting in real time defective eggs in a poultry farm. The first step of the algorithmic process is devoted to the detection of the egg shape to fix the region of interest. A color processing is then performed only on the eggshell to obtain an image segmentation that allows the discrimination of defective eggs from clean ones in critical time. The results are presented to demonstrate the validity of the proposed visual process on a wide sample of both defective and non-defective eggs.