This project focuses on developing a scene recognition system using Python and OpenCV. The aim is to classify images of different scenes—such as beaches, mountains, restaurants, and roads—by leveraging various image processing techniques, including histograms, color moments, texture features, and contours. The project compares multiple approaches from different team members, each implementing a distinct algorithm to enhance the scene classification accuracy.
Key features of the project include:
Histogram-based scene recognition. Color and texture feature extraction. Contour detection and classification. Evaluation and comparison of algorithms through confusion matrix visualization. Modular design for flexibility in feature extraction and classification. This repository includes Python scripts for feature extraction, image classification, and performance evaluation.