Video shot boundary detection using gray level cooccurrence matrix

Abstract

Objectives: The objective of this paper is to find out the abrupt transitions between consecutive shots in a video with less false detection and high F1 score. Method/Analysis: This paper presents a video shot boundary detection approach using Gray Level Cooccurrence Matrix (GLCM). The proposed system can roughly be divided into feature extraction using GLCM and the application of the abrupt shot boundary detection. In the first step, the frames are converted into gray level and GLCM is calculated from each frame in the video. Secondly, correlation coefficient is calculated from the GLCM of two consecutive frames of the video. A threshold is set to identify the shot boundaries of the video. The proposed system can detect abrupt transitions effectively with less false detection in the uncompressed domain. Findings: The proposed system can able to achieve an average F1 score of 93.51%, which is achieve due to the reduced false detection. Novelty/Improvement: The proposed system uses the GLCM matrix directly instead of calculating the contrast, entropy,etc, i.e., the proposed system is purely based on the correlation of the pixel's co-occurrence. The proposed system also reduces the false detection thereby increasing the precision and F1 score.