Automatic focusing method and device based on RBF neural network

A neural network and auto-focusing technology, applied in color TV parts, TV system parts, TV and other directions, can solve the problems of increasing the amount of calculation, easy to fall into local extreme points, etc., saving time and reducing motor movement the effect of the number of times

Inactive Publication Date: 2020-05-12
GUANGDONG UNIV OF TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the prior art, the commonly used algorithm for focusing the camera is the hill-climbing algorithm, which requires the motor to move back and forth frequently to find the best focus point, and it is easy to fall into the local extreme point; the curve

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  • Automatic focusing method and device based on RBF neural network
  • Automatic focusing method and device based on RBF neural network
  • Automatic focusing method and device based on RBF neural network

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Embodiment Construction

[0038] In the industry, cameras are often used to do repetitive tasks. Every time the camera is turned on, it will automatically focus on the inherent target environment, that is, to reach the peak of image clarity, and then perform various adjustments on it after obtaining a clear picture. kind of operation. In order to avoid the influence of the local peak problem existing in the traditional focus search algorithm, such as figure 1 As shown, the application provides a kind of auto-focusing method based on RBF neural network, and this method can be applied to the auto-focusing of industrial camera, and described method comprises:

[0039] S1, acquiring the image of the position to be photographed, and calculating the corresponding focus evaluation value and average gray value according to the image;

[0040] S2, input the focus evaluation value and the average gray value into the preset RBF neural network model, and the RBF neural network model outputs the position where the...

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Abstract

The invention discloses an automatic focusing method and device based on an RBF neural network, and the method comprises the steps: obtaining an image photographed at a position where an objective lens is located, and calculating a corresponding focusing evaluation value and an average gray value according to the image; inputting the focusing evaluation value and the average gray value into a preset RBF neural network model, wherein the RBF neural network model outputs the position of an objective lens at an optimal focusing point; and the objective lens is driven to be adjusted to the position of the optimal focus point by using a zoom motor. According to the application, the influence of a local peak value in an existing focusing search algorithm can be effectively avoided, the frequencyof back-and-forth movement of the zoom motor can be effectively reduced, and the focusing time is shortened.

Description

technical field [0001] The present application relates to the field of industrial automation and auto-focus, in particular to an auto-focus method and device based on RBF neural network. Background technique [0002] In industrial automation, in many cases, it is necessary to automatically focus the camera to obtain a clearer image for subsequent image recognition and processing. [0003] In the prior art, the commonly used algorithm for focusing the camera is the hill-climbing algorithm, which requires the motor to move back and forth frequently to find the best focus point, and it is easy to fall into the local extreme point; the curve fitting search method has a great impact on focusing The position fitting in the flat area of ​​the evaluation function curve is invalid, and it will also be affected by the local peak. To improve the fitting effect will increase the amount of calculation. Contents of the invention [0004] The purpose of this application is to provide an...

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Application Information

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IPC IPC(8): H04N5/232
CPCH04N23/67
Inventor 温泽鑫周延周张道森谢侃谢胜利
Owner GUANGDONG UNIV OF TECH
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