Multi-dimensional Optimization of a Visual Model for Measurement Assurance of Model-Specific Test Equipment that Integrates Data Flow Information Analysis

Multi-dimensional optimization of a visual model for measurement assurance of model-specific test equipment that integrates data flow information analysis is the focus of this study. According to the different emphases of the 3D reconstruction of the model, this study considers 3D reconstruction of plant based on the model, the 3D reconstruction of the plant based on the image and the 3D reconstruction of the plant based on the scanning data set. All work done to then achieve the required measurement accuracy. Furthermore, for the graph cut, the considered algorithm uses the method of adding the edges, that is, continuously adding the edge with the smallest weight while ensuring that no loops are generated. Its fundamental purpose is to ensure product quality, improve efficiency, and improve the general level. Model cost accounting and management should speak with the data. Hence, the measurement assurance of model-specific test equipment is then implemented. Through the systematic model, the performance is tested. This study describes the properties of the experimental benchmark graph and also test the cutting performance.