Road Surface Crack Detection and Identification System Design

This experimental demonstration showcases the application of image processing-based crack detection technology. In this experiment, we demonstrate how to utilize image processing techniques to detect cracks on road surfaces. Our analysis reveals that road cracks typically exhibit characteristics such as branching patterns, fine discontinuities, irregular distribution, and low contrast. To enhance crack target regions, we implemented a series of image preprocessing steps including noise reduction using Gaussian filters, contrast enhancement through histogram equalization, and morphological operations for crack segmentation. These preprocessing steps significantly improve the automation level of road crack inspection, making it more accurate and efficient. Furthermore, we developed a GUI interface using MATLAB's App Designer framework to integrate and demonstrate software functional modules. The system architecture incorporates database connectivity through ODBC/JDBC drivers, enabling persistent data storage and retrieval operations. This implementation approach provides substantial versatility, allowing adaptation to various scenarios and requirements through configurable parameter settings and modular algorithm components.