Research And Implementation Of Grain Size Detection Method Based On Skeleton Extraction

With the rapid development of transportation industry, Asphalt Pavement has become the main pavement form of urban road in our country. The quality of asphalt pavement is naturally becoming the center of people's attention. In asphalt pavement material composition, the aggregate grain morphology, grain size on the performance of the asphalt surface plays a decisive role. Therefore, the aggregate grain size detection is very important. This thesis will be to research deeply on the aggregate grain size detection.In this thesis, through the research about grain size detection based on the skeleton extraction and the characteristics of the grain size of aggregate, aggregate grain size detection skeleton image system is designed. This system has good versatility, reliability and scalability. On the basis of the study of the skeleton image of aggregate,design the aggregate grain size detection method based on skeleton extraction, this method can more accurately measure the grain size. At the same time, display and analysis between the experimental data about aggregate grain size detection and the caliper measurement of grain size of aggregate data, to calculate the parameters correlation between experimental data and real data. By establishing the multiple linear regression equation between the parameters to improve the accuracy of the experimental data.In order to verify the accuracy of the algorithm based on the skeleton extraction algorithm, do the analysis with correlation calculation between experimental data and actual measurement data. By making continuous improvements, the designed scheme about research and implementation grain size detection method based on skeleton extraction in this thesis, on the premise of ensure testing quality and efficiency, realize the efficiency and reliability of detection, for the study of aggregate grain size detection technology to provide technical reference in the future.