Keyframe Extraction Using Color Feature Methods

This article discusses a video keyframe extraction method based on color feature analysis, implemented using MATLAB programming language. Video keyframe extraction represents a crucial task as it enables the identification of representative frames that can effectively summarize entire video content, thereby enhancing video retrieval and classification efficiency. The proposed methodology employs color feature extraction techniques to identify keyframes through computational approaches involving color histograms and color moments. From an implementation perspective, the MATLAB code typically involves processing video frames sequentially, calculating color distributions using histogram analysis (often with RGB or HSV color spaces), and computing statistical color moments to capture additional color characteristics. The algorithm compares color feature vectors between consecutive frames using distance metrics like Euclidean or Chi-square distance to detect significant content changes. Key MATLAB functions employed in this process may include VideoReader for video input, rgb2hsv for color space conversion, imhist for histogram calculation, and pdist2 for feature comparison. This approach provides deeper insights into video content analysis while facilitating more efficient video management and categorization through automated keyframe selection.