Classification of Overlapping Eggs Based on Image Processing - B Purahong; W Krungseanmuang; V Chaowalittawin; T Pumee; Isoon Kanjanasurat; A Lasakul (Journal of Physics Conference Series, 2022)
Abstract This paper presents a method for classifying the overlapped eggs and counting the number of eggs on the conveyor belt using image processing techniques. The image was acquired by a webcam camera that connected to the computer and then rescaled. The image was then converted to grayscale and noise was reduced using a Gaussian blur filter. Otsu’s Binarization is used to convert the image to binary. The binary image is then subjected to morphological operations. Following that, using the Watershed Algorithm, separate the egg’s overlapped area. Finally, the prepared image is ready to be counted using the contour matrix method. This method independently classifies each egg segmentation and can count up to 18 eggs per frame with a processing time of less than 1 second.
Keywords: Smart Agriculture and AI; Spectroscopy and Chemometric Analyses; Digital Imaging for Blood Diseases