High-speed Video Keyframe Extraction Based on K-means
Aiming at the high-speed images generated in the range static explosion experiment,an improved K-means high-speed image clustering method is proposed,which completes the extraction of high-speed video keyframes by fusing and opti-mizing the K-means algorithm of the initial cluster center and the cluster upper bound based on the AP algorithm.The upper bound of the cluster dataset is determined firstly,and then the keyframe extraction of the initial center of the optimization is performed with-in the clustering range.Finally,the clustering effect is evaluated by CH index,accuracy rate,recall rate,and F1 value,and the evaluation results show that compared with the traditional algorithm,the improved algorithm has higher clustering accuracy and exe-cution efficiency.
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