Research And Application On Image Recognition And Milling Of Calf Bone Slice

Bone defects caused by trauma,tumors,congenital malformations and other causes can seriously affect health.While autologous,allogeneic,and xenografts are generally accepted for bone repair,biological implants may still have problems lacking bone origin,carrying pathogens,or causing immune rejection.With the rapid development of tissue engineering technology,bone tissue engineering has become an important method for the treatment of bone defects in recent years.Bionic scaffolds made of bone meal have good compatibility with human tissues and relatively low production costs.Bone meal is currently a widely used bone graft biomaterial,and it is also the most studied bone grafting biomaterial so far.The cancellous bone in calf bone is the main raw material for bone meal processing,and most of the current cutting of bone pieces in calf bone is completed manually,which consumes a lot of manpower and causes a large amount of cancellous bone waste.Image processing technology has been applied to workpiece identification and inspection,most of them for defect detection,according to the characteristics of calf bone pieces of different sizes and shapes,there is no suitable technology to accurately extract the edge of cancellous bone and use CNC machine tools for processing.In this thesis,image processing technology is mainly used to identify the edges of cancellous bone in calf bone pieces,and the corresponding processing routes are generated according to different edges and milling is completed.The main research contents of this thesis are as follows:(1)Acquisition and preprocessing of calf bone images.Firstly,the calf bone pieces are shot one by one,and the RGB images taken by using python language through pycharm software are converted into GGRAY and HSV images,and the calf bone pieces in the two color spaces are compared,and the saturation channels(S channels)in the three channels of H,S and V are finally extracted according to the characteristics of simple calf bone color,and the median filter is selected for image denoising by comparing the effects of mean filtering,Gaussian filtering and median filtering denoising,in order to make the edge detection clearer The image is further thresholded,and the OTSU algorithm is selected to complete the image thresholding process by comparing the results of binary thresholding and OTSU thresholding,and finally complete the image segmentation.(2)The detection operator of cancellous bone edge in bone pieces was selected and optimized.The first-order edge detection operator and the second-order edge detection operator are introduced respectively,and the sobel operator in the first-order edge detection operator,the LOG and Canny operators in the second-order edge detection operator are used to compare the effect of the calf bone fragment image after image segmentation.The Canny edge detection operator with accurate positioning and clear detection edge was selected,and the Canny operator was improved so that the extracted cancellous bone edge was the only edge in the image.Finally,cancellous bone margin extraction was performed on images of four bone pieces of different shapes and sizes.(3)Generate a processing route based on the bone edge detection image.From the aspect of tool material and type analysis to determine the bone milling using flat bottom four-edged carbide end mill,analyze the characteristics of bone material and bone milling kinematics,select the appropriate processing parameters,in order to reduce the milling force and at the same time to ensure the processing efficiency,select the machining feed speed of 3000mm/min,the depth of eating tool is 4mm,and the spindle speed is selected according to the type of machine tool is 24000r/min.Finally,two random images of cancellous bone edges were used to identify them by JDPaint software,convert the 2D images into 3D machined surfaces and set the selected parameters,generate the machining route and export the NC code.Based on the actual situation,according to the needs of enterprises,this thesis proposes a design method for automatic recognition of calf bone pieces,and completes the milling process.It can greatly reduce the repetitive work of workers,improve the efficiency of cancellous bone extraction,make the processing process more automated,meet the needs of enterprises for cancellous bone extraction,and increase the competitiveness of enterprises.