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Image search method based on deep learning

A technology of image search and deep learning, applied in the field of image search based on deep learning, can solve problems such as low query efficiency, impact on bandwidth and marking ability, and reduce work efficiency, so as to improve query efficiency, reduce data collection samples, and bandwidth and bidding capacity savings

Active Publication Date: 2017-05-31
杭州中奥科技有限公司
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Problems solved by technology

[0007] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art, and provide a deep learning-based image search method, which aims to solve the problem that the traditional image search method in the prior art is affected by the limited bandwidth and marking ability, resulting in query efficiency Low, technical problems that reduce work efficiency

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  • Image search method based on deep learning

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[0028] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. However, it should be understood that the specific embodiments described here are only used to explain the present invention, and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.

[0029] refer to figure 1 , the embodiment of the present invention provides a deep learning-based image search method, the method comprising the following steps:

[0030] Step 1. Enter the vehicle information to be searched.

[0031] Wherein, the search information includes pictures and keywords of the vehicle to be searched, and the keywords include the license plate number, vehicle brand, ...

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Abstract

The invention discloses an image search method based on deep learning. The image search method greatly enhances the search efficiency through information input, searching strategies, search, result discrimination and output to a GIS database. A traditional image search method is low in query efficiency and reduces work efficiency because collected sample data is huge and the bandwidth and the scaling capacity are limited. The disclosed image search method has the advantages that the accuracy in the image search process and recognition quality are improved through deep learning; the searching strategies include distance and road preceding-following relations, and images can be searched according to specific situations; under the situations like dense roads, the road preceding-following relation search strategy is adopted, the distance search strategy is used in open regions, the quantity of collected data samples are greatly reduced, and the search speed is increased; distributed-type search and centralized-type search can be utilized for the image search, the appropriate search approach is selected according to actual conditions, accordingly the bandwidth and the scaling capacity are saved, and the query efficiency is greatly improved.

Description

[0001] 【Technical field】 [0002] The present invention relates to the technical field of image search, in particular to an image search method based on deep learning. [0003] 【Background technique】 [0004] In current traffic management and road planning, traffic flow and the type and speed of passing vehicles are important parameters. The methods of automatically obtaining these data can be roughly divided into two categories: one is to use sensors such as piezoelectric, infrared, and ring magnetic induction coils to obtain the parameters of the vehicle itself. This method has a high tracking and recognition rate, but is easy to damage and inconvenient to install. ; There is also a method based on image processing and pattern recognition, which overcomes the limitations of the previous method. Due to the advancement of image processing and recognition technology and the substantial increase in hardware cost performance, systems with certain practical value have emerged. The...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/5838G06F16/5866
Inventor 沈贝伦陆韵沈俊青宋冠弢张登
Owner 杭州中奥科技有限公司
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