Crack Detection of Eggshell using Image Processing and Computer Vision - B Purahong; V Chaowalittawin; W Krungseanmuang; P Sathaporn; T Anuwongpinit; A Lasakul (My University, 2022)
Abstract This article presents an eggshell crack inspection using image processing techniques. This approach uses the concept of industrial 4.0 to reduce manual coordination in the egg industry’s manufacturing process. The method started with receiving images from a webcam camera. Then, we rescaled the image to 1147 x 633 for faster computation. Next, divide the image into the red and green channels. The red channel image was converted to grayscale using a Gaussian blur filter with a kernel filter 11 x 11 to reduce noise, followed by turning the image to binary. After that, multiply the binary image with the grayscale of the green channel to remove the background. By that time, a morphological operation was used to enhance the quality of the image. Finally, use the contour matrix to find the area of the object and then build the condition to detect the crack in the eggshell. These techniques of image processing are used to inspect the eggshell crack with a high accuracy of more than 98% as well as the high performance of computing.
Keywords: Kernel (algebra); Gaussian filter; Infrastructure Maintenance and Monitoring