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Deep learning-based image fuzzy region detection method and apparatus

A detection method and technology of blurred area, applied in the field of image recognition, can solve the problem of fast and effective recognition of blurred images.

Active Publication Date: 2016-11-09
高前文
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

Unable to quickly and efficiently identify blurred images

Method used

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  • Deep learning-based image fuzzy region detection method and apparatus
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  • Deep learning-based image fuzzy region detection method and apparatus

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Embodiment Construction

[0096] All features disclosed in this specification, or steps in all methods or processes disclosed, may be combined in any manner, except for mutually exclusive features and / or steps.

[0097] Any feature disclosed in this specification, unless specifically stated, can be replaced by other alternative features that are equivalent or have similar purposes. That is, unless expressly stated otherwise, each feature is one example only of a series of equivalent or similar features.

[0098] Relevant description of this patent:

[0099] 1. DI 1 ...BL 1 ... SA ii ,Q ii1 ,Q ii2 , R ii0 , R ii1 , R ii2 , CH ii1 , CH ii2 , CH ii3 ,CH ii The size is m*n;

[0100] 2. The Garbor filter has two important parameters: the size and direction of the convolution template. Here the size of the convolution template is taken as z*z (z=5,7,9,11,13,15,17,19), and 8 (when xx=8) directions (0 degrees, 25 degrees, 50 degrees, 75 degrees, 100 degrees, 125 degrees, 150 degrees, 175 degrees...

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Abstract

The invention relates to the field of image identification, in particular to a deep learning-based image fuzzy region detection method and apparatus. The invention provides the deep learning-based image fuzzy region detection method and apparatus for the problems existent in the prior art. The method mainly comprises the following steps of creating a sample picture set; performing gabor filtering and creating a 4-channel image according to multi-scale information; constructing a deep convolutional network to learn image characteristics, performing training by taking the obtained sample 4-channel image as an input of the deep convolutional network, and generating an optimal model of a deep learning network; performing regional small block extraction on an image required to be identified, establishing a 4-channel image, inputting the established 4-channel image in the optimal model of the deep learning network, and obtaining a classification result; and analyzing the classification result to obtain a fuzzy attribute and a clear region of the to-be-identified image.

Description

technical field [0001] The invention relates to the field of image recognition, in particular to a method and device for detecting image blurred areas based on deep learning. Background technique [0002] With the development of science and technology and the continuous progress of the times, video and image data processing technology has gradually matured and plays an important role in people's life and work. In the future, the connection between video surveillance and our lives will become increasingly close. There is no doubt that the research and development of video image processing technology is one of the biggest security hotspots nowadays, and it is also an area worthy of attention by many security companies. [0003] In the field of security, most of the equipment needs to be installed outdoors, and the equipment needs to withstand the wind and sun all year round. It has to experience the influence of natural conditions such as perennial temperature, humidity, sal...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/32G06K9/46
CPCG06V10/457G06V10/25G06V10/56
Inventor 史方乔宝华王标
Owner 高前文
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