CONCRETE CRACK DETECTION TECHNIQUES USING IMAGE PROCESSING AND MACHINE LEARNING ALGORITHMS

This project presents an intelligent system for detecting cracks in concrete structures using image processingtechniques combined with machine learning algorithms such as Support Vector Machine (SVM) andConvolutional Neural Networks (CNN). Developed in Python using the Visual Studio platform, the systempreprocesses input images through steps like gamma correction, grayscale conversion, and noise reduction toenhance crack visibility. It then uses SVM for binary classification of crack regions and a CNN model to improveprecision in localized patch-based crack detection. This approach automates structural inspection with highaccuracy and reliability.