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Image blurring type identifying and parameter setting method based on fusion memory CNN

A technology of type identification and parameter tuning, applied in image data processing, image enhancement, image analysis, etc., can solve the problem that the network does not have independent memory function.

Active Publication Date: 2017-10-20
JIANGXI UNIV OF SCI & TECH
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Problems solved by technology

[0005] The purpose of the present invention is to provide an image fuzzy type recognition and parameter setting method of fusion memory CNN, which is used to overcome the shortcomings of the existing fuzzy recognition network without independent memory function, and can improve the efficiency of image fuzzy type and parameter calculation

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  • Image blurring type identifying and parameter setting method based on fusion memory CNN
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  • Image blurring type identifying and parameter setting method based on fusion memory CNN

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Embodiment Construction

[0053] The invention adopts an image fuzzy type recognition and parameter setting method of fusion memory CNN to overcome the disadvantage that the network does not have a memory function in the existing fuzzy recognition.

[0054] The present invention will be described in detail below in conjunction with an example (track surface defect detection).

[0055] The first step is to build a fusion memory network architecture:

[0056] The fusion memory CNN model is divided into a serial architecture of 5 convolutional layers, 1 deep memory network and 1 BP network;

[0057] The first convolution layer selects 96 convolution operators, and each convolution operator is a 16×16 convolution kernel. The convolution kernel contains 72 different shapes of straight lines and 8 different sizes of disks and 16 A ring of different shapes, each convolution kernel extracts the first-level shape feature of the image sub-image unit;

[0058] The second convolution layer selects 256 convolutio...

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Abstract

The invention relates to the field of blurred image type identification and parameter calculation, in particular to an image blurring type identifying and parameter setting method based on a fusion memory CNN (Convolutional Neural Network). The method includes the following steps: building a fusion memory network framework; setting an algorithm for each layer of the fusion memory network; getting network parameters through network training; and identifying the blurring type of an unknown image and setting the parameters. The method overcomes the problem that the network in the existing blurring identification has no independent memory function, and can improve the efficiency of image blurring type identification and parameter calculation.

Description

technical field [0001] The invention relates to the field of fuzzy image type identification and parameter calculation, in particular to an image fuzzy type identification and parameter setting method of fusion memory CNN (convolutional neural network). Background technique [0002] Today, with the rapid development of network and information technology, CCD and CMOS have become the mainstream core sensors after pressure and current sensors are used in various fields, whether in aerial photography or unmanned vehicles, popular face recognition, text recognition It is also a variety of industrial inspection camera applications, as well as mobile phone camera applications. However, due to the influence of various factors such as the environment, the collected images are not very clear, especially the images collected under the environment of high-speed camera movement contain serious fuzzy information, which brings great difficulties to the next application. Therefore, it is ...

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Application Information

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IPC IPC(8): G06T5/00G06N3/04
CPCG06T5/00G06T2207/20056G06T2207/20088G06N3/045
Inventor 黄绿娥鄢化彪吴禄慎陈华伟袁小翠朱根松
Owner JIANGXI UNIV OF SCI & TECH
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