Medial Axis Transform

1 Nov 2024 – 15 Dec 2024

Project Overview

The Medial Axis Transform project is a final project for COMP 558 (Computer Vision) at McGill University. The main goal is to replicate and build upon the findings of the paper “Shape-Based Measures Improve Scene Categorization” by exploring additional geometric properties in images.

Full Report and source code

For a comprehensive project overview, please Project Report. Source code would be available at GitHub Repository.

Project Presentation

Objectives

• Replication: Recreate the experiments from the referenced paper to establish a baseline.
• Innovation: Propose a new geometric property, Convexity, to complement traditional Gestalt cues.
• Evaluation: Investigate the impact of these geometry cues on enhancing CNN model performance through rigorous experiments.

Technical Approach

• Data Analysis: Employ image processing techniques to extract and analyze relevant geometric features.
• Model Training: Integrate the new geometric property into CNN models and evaluate performance gains.
• Comparative Study: Compare results with baseline approaches to ascertain the effectiveness of the proposed cue.

Outcomes

This project aims to bridge theoretical insights and practical implementation, ultimately contributing to the field of computer vision by offering improved methods for scene categorization.