Image-tampering-detection

This Python project employs machine learning and computer vision to detect image tampering, classifying images as "Authentic" or "Tampered." It features comprehensive preprocessing, including resizing and normalization, and uses a Support Vector Machine (SVM) classifier with a linear kernel for classification. The system includes features like color histograms, LBP histograms, sharpness, and brightness. Evaluation metrics include accuracy, precision, recall, and F1 score.