Cracked egg recognition based on machine vision

Abstract

Abstract Since the cracks on eggshell are difficult to be recognized due to the surrounding highlighted dark spots on the egg surface under back-light illumination, a new method to identify the cracks based on machine vision was proposed. After analyzing the characteristics of the cracks in the image of the egg under the back-light illumination, a negative LOG (Laplacian of Gaussian) operator was employed to effectively enhance the cracks in the egg image. Then the Hysteresis thresholding algorithm was adopted to acquire the proper thresholds, which eliminated the irrelevant dark spots in the binary egg image and ensured the continuity of the cracks. Finally, the improved LFI (Local Fitting Image) index was used to distinguish the crack region from the mislabeled region. The experimental results showed that the proposed method was effective in cases of complicated egg surface conditions, such as irregular dark spots and invisible micro-cracks, with cracked egg recognition rate of 92.5%.