Research On Inspection Methods Of Egg Exterior Quality Based On SVM

quality is higher than before. Paper have improved experiment device and egg weight, egg shape as well as eggshell color are studied respectively using machine vision technology. Contents specifically are following:Experiment device is improved. The annular fluorescent lamp is selected as light source. Through adjusting the related parameter of Baslar image gather software as well as the altitude of object table and the focal length of camera, vivid egg images are gotten. Camera calibration is done for experiment device, and its accuracy is less than 0.1mm which can satisfy the requirement of egg exterior quality inspection.The captured egg images are pre-processed with the method of conversion of color space, gray transform, declining noise and binarization. A new method is put forward for binarization. Firstly, the saturation weight of egg image is distilled in HSV color space, and then Ostu algorithm and mathematic morphologic method are used for obtaining binarization image.The feature parameters of egg shape, weight and eggshell color are studied. Classification models are established by using support vector machine algorithm, and standard BP and GA-BP algorithm are used to do contrast experiment. Results demonstrate that the train accuracy and test accuracy of support vector machine algorithm is better. For the detection of egg shape, weight and eggshell color, classification accuracy can arrive at 100%, 98.21% and 97.14% respectively.