Precise Inspection of Geometric Parameters for Polyvinyl Chloride Pipe Section Based on Computer Vision

Abstract

The precise inspection of geometric parameters is crucial for quality control in the context of Industry 4.0. The current technique of precise inspection depends on the operation of professional personnel, and the measuring accuracy is restricted by the proficiency of operators. To solve the defects, this paper proposes a precise inspection framework for the geometric parameters of polyvinyl chloride (PVC) pipe section (G-PVC), using low-cost visual sensors and high-precision computer vision algorithms. Firstly, a robust imaging system was built to acquire images of a PVC pipe section under irregular illumination changes. Next, an engineering semantic model was established to calculate G-PVC like inner diameter, outer diameter, wall thickness, and roundness. After that, a region-of-interest (ROI) extraction algorithm was combined with an improved edge operator to obtain the coordinates of measured points on PVC end-face image in a stable and precise manner. Finally, our framework was proved highly precise and robust through experiments.

Dimensionality Reduction and Extraction of Engineering Remote Sensing Data Based on Building Information Modeling and Geographical Information System

“…Feature compression and extraction is an important way to analyze massive remote sensing data [10]. As a spatial database technique, the GIS can store a huge amount of 3D spatial data and manage and visualize the massive data effectively [11,12]. us, it plays an important role in the management and analysis of urban construction land.…”