Detection of Surface Defects in Eggs Using Computer Vision

컴퓨터 시각을 이용한 계란 표면의 결함 검출

A computer vision system was built to generate images of a stationary egg. This system includes a. CCD camera, a frame grabber, and an incandescent back lighting system An image processing algorithm was developed to accurately detect surface holes and surface cracks on eggs. With 20W of incandescent back light, the detection rate was shown to be the highest. The Sobel operator was found to be the best among various enhancing filters examined. The threshold value to distinguish between the crack and the translucent spots was found to be linear with the average gray level of a whole egg image. Those values of both gray level and area were used as criteria to detect holes in egg and those values of both area and roundness were used to detect cracks in egg. For a sample of 300 eggs, this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. On the average, it took 59.5 seconds to analyze an egg image and determine whether or not it was defected.