Nondestructive detecting cracks of preserved eggshell using polarization technology and cluster analysis

Abstract: Pickled egg had lots of beige spots and some large black spots on its eggshell, so it is difficult to detect cracks on the preserved eggshell. A polarization optical system was designed to obtain images, and the system was tested by the Malus law. Polarization optical system was used to acquire images on different polarization angles, including 0, 45°, ?45°and 90°, and then the Stokes images and polarization images were processed by image fusion technique with the Stokes Formula. According to different depolarization mechanisms for black spots and cracks on preserved eggshell, it can distinguish black spots and cracks on the polarization image. The most connected area of high gray value was taken as the center to cut an image about 100×100 pixel area. Four characteristic parameters were extracted to distinguish the cracks on preserved eggshell, including the length of the crack, mean variance ratio, skewness and kurtosis. We put forward 4 characteristic parameters and use the cluster analysis to detect cracks. Info-Kmeans clustering algorithm was used in this study, and the clustering of high-dimensional sparse data were extracted from the images. The results showed that all preserved eggs were classified into intact and cracked groups, and the accuracy rate was 93%. In this experiment, the sensitivity and specificity were 100% and 88.3%, the detection rate of intact preserved egg was 100%. The validation experimental result showed that the accuracy was 94%, and the sensitivity and specificity were 100% and 88.3%. Results showed that the model could distinguished intact and cracked preserved eggs efficiently, and it was great potential to detect cracks on product lines.