A subtitle matching method and system based on image retrieval

An image retrieval and matching method technology, applied in the field of image processing, can solve the problems of inability to apply automatic image subtitle matching, poor range expansion, etc., and achieve the effect of reducing manual operation time, improving accuracy, and fast image subtitle matching.

Active Publication Date: 2018-06-01
XIAMEN MEITUZHIJIA TECH
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Problems solved by technology

Although the above-mentioned hash algorithms are proposed from different angles of the problem, they all have their own characteristics and advantages, but they are often only effective on certain specific setting conditions or databases, and have poor range expansion and cannot be applied to image processing. Automatic subtitle matching

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  • A subtitle matching method and system based on image retrieval
  • A subtitle matching method and system based on image retrieval

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[0048] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention clearer and clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0049] Extreme Learning Machine (Extreme Learning Machine) ELM is an algorithm for solving a single hidden layer neural network proposed by Huang Guangbin. The biggest feature of ELM is that for traditional neural networks, especially single hidden layer feedforward neural networks (SLFNs), the extreme learning machine only needs to set the number of hidden layer nodes of the network, and does not need to adjust the input weight of the network during the algorithm execution process. value and the bias of the hidden element, and produce the only optimal ...

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Abstract

The invention discloses a subtitle matching method and system based on image retrieval. By acquiring the image to be matched, the sample image and the subtitle content corresponding to the sample image, the collected sample image is used as the data for ELM self-encoding network training, and the subtitle content to be matched is The image and each sample image are respectively trained with the ELM self-encoding network to obtain a hash function, and the hash function is used to convert the binary code of the image to obtain the binary code sequence of the image to be matched and each sample image, and calculate the Chinese between the calculated images. According to the Hamming distance, similar image retrieval is carried out by the K nearest neighbor method to obtain the most similar sample image with the image to be matched, and finally the subtitle content corresponding to the most similar sample image is given to the image to be matched; The accuracy of image similarity retrieval, and the use of binary coding ensures the efficiency of retrieval and achieves the effect of fast and accurate image subtitle matching.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a subtitle matching method based on image retrieval and a system applying the method. Background technique [0002] The most critical point of matching a suitable video subtitle for a specific image is the efficiency and accuracy of image retrieval. The data resources of video subtitles are very large, and it is difficult for users to find the information they are really interested in in the vast amount of data. Therefore, how to quickly and efficiently analyze and retrieve massive images has become a very challenging task. [0003] Traditional content-based image retrieval techniques often extract the underlying features of images for exhaustive comparison, but because the time complexity of the comparison process is linear, they cannot be extended and applied to large-scale network image data, and Since the underlying visual features of images are often tens of thousa...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06K9/62
Inventor 张伟曾志勇张长定傅松林
Owner XIAMEN MEITUZHIJIA TECH
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