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Video key frame extraction method based on color quantization and clusters

A video key frame, color quantization technology, applied in digital video signal modification, television, character and pattern recognition, etc., can solve the problem of ineffective preservation of image sequence and dynamic information.

Inactive Publication Date: 2013-04-24
SOUTHWEAT UNIV OF SCI & TECH
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Problems solved by technology

The clustering method has high computational efficiency and can effectively obtain the visual content of the video shot with significant changes, but it cannot effectively preserve the image order and dynamic information of the image frames in the original shot

Method used

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  • Video key frame extraction method based on color quantization and clusters
  • Video key frame extraction method based on color quantization and clusters
  • Video key frame extraction method based on color quantization and clusters

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Embodiment Construction

[0061] Below in conjunction with accompanying drawing, the present invention is described in further detail:

[0062] Such as figure 1 As shown, a kind of video key frame extracting method based on color quantization and clustering of the present invention comprises the following processes:

[0063] Load the video data stream → scan the video stream for a single frame → perform color quantization on the obtained frame image, extract the main color features of the quantized frame image → calculate the similarity between adjacent frames, and obtain the difference between adjacent frames → according to the adjacent Shot boundary detection for frame difference → shot classification for the segmented shot sequence, extracting representative frames of each shot → compressing and clustering representative frame sequences to obtain key frame sequences.

[0064] 1. For the loaded video stream data, first perform single-frame scanning 101;

[0065] 2. Carry out color quantization 102 ...

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Abstract

The invention discloses a video key frame extraction method based on color quantization and clusters. The method comprises the steps of loading video data flow; conducting single frame scanning on video flow; conducting the color quantization on obtained frame images, and extracting main color features of the frame images going through quantization; calculating similarity of adjacent frames so as to obtain adjacent frame difference; conducting shot boundary detection according to the adjacent frame difference; conducting shot classification on intersected shots and extracting a representative frame of each shot; and conducting compression clustering on the sequence of the representative frames so as to obtain a key frame sequence. According to the method, the color quantization is conducted on the single frame images so that main color of the images is extracted, frame difference calculation is conducted through the cluster feature similarity calculation method based on color features of the clusters so that the shot boundary detection is realized, and finally clustering according to the compression ratio is conducted on the extracted representative frames. Due to the fact that he whole process is low in dependency on video formats and types, the method has good universality and adaptability, is simple in calculation and low in space consumption, and can effectively avoid the phenomenon of key frame selection redundancy, control the number and quality of the key frames, and realize control of the video compression ratio.

Description

technical field [0001] The invention relates to a video key frame extraction method, in particular to a video key frame extraction method based on color quantization and clustering which can extract key frame sequences from videos of different types and different resolutions. The invention belongs to the field of video key frame extraction. Background technique [0002] With the large number of applications of multimedia information in entertainment, commerce, production, medicine, security, national defense, military and other fields, the traditional video retrieval scheme based on keyword description has a large workload due to manual annotation and strong subjectivity in artificial text label description. , Low efficiency and many other defects can no longer meet the needs of massive video retrieval. How to effectively store, organize, manage, browse and retrieve video information has become a key issue. Content-based video retrieval provides a feasible way to solve this...

Claims

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Application Information

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IPC IPC(8): G06K9/62H04N7/26H04N19/159
Inventor 吴亚东王松韩永国陈永辉
Owner SOUTHWEAT UNIV OF SCI & TECH
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