Motion compensated image processing and optimal parameters for egg crack detection using modified pressure

Abstract

Shell eggs with microcracks are often undetected during egg grading processes. In the past, a modified pressure imaging system was developed to detect eggs with microcracks without adversely affecting the quality of normal intact eggs. The basic idea of the modified pressure imaging system was to apply a short burst of vacuum within a transparent chamber in order to cause a momentary and forced opening in the egg shell with a crack and thus to utilize the changes in image intensities during this process. The intensity changes from dark to bright in the shell surface were recorded by a high-resolution digital camera and processed by an image ratio technique. However, the performance of the imaging system was compromised by both false readings due to motion of intact eggs relative to the camera and an improper selection of parameter values for the detection algorithm. First, a machine vision technique based on motion estimation of individual eggs was developed to compensate any motion errors present on images and thus reduce false crack-detection readings. The simulation results of the developed motion estimation and compensation technique with 3,000 eggs showed no false errors. Second, the receiver operating characteristic (ROC) curve was used to evaluate and compare the performance of the crack-detection algorithm under varying parameters (ratio and detection-tolerance thresholds) and to find the optimal parameter values. The area under the ROC curve (AUC) was used to compare the performance under varying parameter values. The minimum distance and Youden index criteria were used to find the optimal values from the ROC curve. The minimum distance criterion found the optimal parameters at 1.11 and 20 (or 1.1 and 25) for the ratio and detection-tolerance thresholds, respectively. The true positive and false positive rates at the optimal conditions were 98.91 and 0.14 %, respectively.