Video Key Frame Extraction Using MATLAB

This document provides a comprehensive guide to implementing video key frame extraction using MATLAB. We demonstrate three distinct methodologies: perceptual hashing, image correlation coefficient analysis, and absolute frame difference calculation. Each method is thoroughly explained with its underlying principles and implementation steps, accompanied by MATLAB code examples to facilitate understanding. The implementation involves reading video files using VideoReader, processing frames sequentially, and applying specific algorithms to identify significant content changes. For perceptual hashing, we convert frames to grayscale, resize them to standard dimensions, and compute hash values using discrete cosine transform coefficients. The image correlation method calculates normalized cross-correlation between consecutive frames to measure similarity. The absolute frame difference approach computes pixel-wise differences and applies thresholding to detect substantial changes. We also analyze the advantages and limitations of each technique, along with their practical applications in different scenarios. Through detailed explanations and code demonstrations, this document aims to provide readers with deep understanding of MATLAB-based video key frame extraction techniques.