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An Accurate Keyframe Extraction Method Based on Hybrid Feature and Mutation Detection

A mutation detection and hybrid feature technology, applied in image communication, selective content distribution, electrical components, etc., can solve problems such as low efficiency and large amount of calculation, achieve high accuracy, improve accuracy, and reduce redundancy degree of effect

Active Publication Date: 2018-07-20
SHANGHAI SHANGDA HAIRUN INFORMATION SYST +3
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  • Application Information

AI Technical Summary

Problems solved by technology

At present, most of the key frame extraction methods are based on the original video stream. Before extracting key frames, a large number of decompression operations must be performed. After decompression, various analysis and processing of video data are performed. not tall

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  • An Accurate Keyframe Extraction Method Based on Hybrid Feature and Mutation Detection
  • An Accurate Keyframe Extraction Method Based on Hybrid Feature and Mutation Detection
  • An Accurate Keyframe Extraction Method Based on Hybrid Feature and Mutation Detection

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Embodiment

[0048] Such as figure 1 As shown, an accurate key frame extraction method based on mixed features and mutation detection is used to manage and index videos, including the following steps:

[0049] 1) Obtain the image frame set of the video sequence of the target video, extract the color features of the image in the video, and calculate the color distance between two adjacent frame images, the color distance d between adjacent two frame images 1 The calculation formula is:

[0050]

[0051] CLD 1 ={DY i ,DCb i ,DCr i}

[0052] CLD 2 ={DY' i ,DCb′ i ,DCr′ i}

[0053] Among them, CLD 1 and CLD 2 is the color feature information of two adjacent frames of images, (DY i ,DCb i ,DCr i ) and (DY′ i ,DCb′ i ,DCr′ i ) is the i-th DCT coefficient obtained after the color components of two adjacent frames of images undergo DCT transformation, w bi ,w ri ,w yi is the weight;

[0054] 2) Extract the texture features of the image in the video, and calculate the texture...

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Abstract

The invention relates to an accurate key frame extraction method based on mixed features and sudden change detection, and aims to realize management and indexing for videos. The method comprises the following steps: (1) acquiring an image frame set of a video sequence of a target video, extracting the color features of images in the video, and calculating the color distances between two adjacent frames of images; (2) extracting the texture features of the images in the video, and calculating the texture distances between two adjacent frames of images; (3) performing normalization processing on the color distances and the texture distances between the two adjacent frames of images to obtain a processed synthetic distance; (4) acquiring an initial key frame according to a set threshold and the synthetic distance through distance accumulation; and (5) performing sudden change detection on the initially-selected key frame to obtain a final key frame. Compared with the prior art, the accurate key frame extraction method has the advantages of high accuracy, low redundancy and the like.

Description

technical field [0001] The invention relates to feature extraction technology, Gabor transformation, mutation detection technology and key frame extraction technology, in particular to an accurate key frame extraction method based on mixed features and mutation detection. Background technique [0002] With the popularization of computers, the development of network and multimedia technology, multimedia information has gradually become one of the common ways for people to disseminate information, accompanied by the explosive growth of video data. Therefore, the demand for scientific and effective management and indexing of a large amount of video data has become increasingly urgent, and key frame extraction technology has emerged as the times require. A key frame refers to the most important and representative image frame in a video shot, which summarizes the content of a certain video to the greatest possible extent. Therefore, a more efficient and convenient method is prov...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N21/234H04N21/44
CPCH04N21/23418H04N21/44008
Inventor 黄曜欧阳杰臣陆蓉蓉卞敏捷
Owner SHANGHAI SHANGDA HAIRUN INFORMATION SYST