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Method for detecting crowding degree of crowds in subway vehicle based on image processing

An image processing and detection method technology, which is applied in the field of image processing to achieve the effects of easy popularization, good use effect, and high detection efficiency and precision

Pending Publication Date: 2021-06-22
李韵涵
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is still a lack of methods in the prior art that can be well applied to the detection of crowd crowding in subway cars.

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  • Method for detecting crowding degree of crowds in subway vehicle based on image processing

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Embodiment Construction

[0041] Such as figure 1 Shown, the crowd crowd degree detection method in the subway car based on image processing of the present invention, comprises the following steps:

[0042] Step 1. Video image acquisition and transmission: Multiple compartment real scene detectors perform real-time detection of the video images in the compartments where they are located, and the image acquisition card performs analog-to-digital conversion on the collected video images and transmits them to the crowded compartment in real time degree recognition computer;

[0043] Step 2, video image preprocessing, the specific process is:

[0044] Step 201, image denoising processing: the computer for recognizing the degree of crowd crowding in the compartment performs low-pass filtering processing on the received video image to obtain a video image after noise removal;

[0045] Step 202, image enhancement processing: the computer for identifying the degree of crowd crowding in the carriage adopts a ...

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Abstract

The invention discloses a subway in-vehicle crowding degree detection method based on image processing. The method comprises the following steps: 1, video image collection and transmission; 2, preprocessing a video image; and 3, the carriage crowd degree recognition computer inputs the crowd target image into a pre-constructed BP neural network model based on fruit fly algorithm optimization, and automatically outputs a crowd degree recognition result. The method is simple in steps, convenient to implement and low in cost, video images of dynamic crowds in the carriage are obtained through the carriage live-action detector, then the crowding degree of the crowds in the subway carriage is predicted through the BP neural network optimized based on the fruit fly algorithm, real-time early warning of the crowding degree of the crowds in the subway carriage is achieved, and the crowding degree of the crowds in the subway carriage is improved. The subway in-vehicle crowding degree detection efficiency and precision are high, the use effect is good, and popularization and use are convenient.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an image processing-based method for detecting crowd crowding in subway cars. Background technique [0002] In recent years, with the improvement of people's consumption level, a large number of people have emerged in shopping malls, supermarkets, bus stations, subways and other places, and the identification of the number of people has gradually become the content of various experts and scholars. As a key technology for identifying the number of people, the purpose of video surveillance analysis technology is to use computer vision technology, video image processing technology and artificial intelligence technology to describe, analyze and understand the content objects of surveillance video, abstract them into identifiable features, and based on The obtained features are used for security warning and real-time control. In addition, in the application of su...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/34G06K9/40G06N3/08
CPCG06N3/084G06V20/53G06V10/30G06V10/267
Inventor 不公告发明人
Owner 李韵涵