Keyframe Extraction Using Euclidean Distance Method

The MATLAB programming language enables keyframe extraction operations based on calculating Euclidean distances between video frames. Keyframe extraction represents a crucial technique in video processing that analyzes differences between frames to select the most representative and information-rich frames. Euclidean distance serves as a commonly used method for measuring differences between two vectors, making it suitable for calculating similarity between video frames. In MATLAB implementation, this approach typically involves converting video frames to feature vectors (such as color histograms or edge descriptors) and computing pairwise Euclidean distances. The algorithm can be structured to identify frames with significant distance changes from their predecessors as keyframes. Key functions involved include video reading (VideoReader), frame difference calculation (pdist2 for Euclidean distance), and threshold-based keyframe selection. Developing this algorithm in MATLAB facilitates automated keyframe extraction processes, significantly enhancing both efficiency and accuracy in video processing tasks. The implementation may incorporate dynamic thresholding mechanisms to adapt to varying video content characteristics and optimize keyframe selection criteria.