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Subway fare evasion behavior detection method and system based on infrared thermal imaging

A technology of infrared thermal imaging and detection method, which is applied in the field of image processing and can solve the problems of pedestrian fare evasion

Active Publication Date: 2019-10-25
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The existing subway monitoring system has not yet solved the problem of pedestrian fare evasion

Method used

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  • Subway fare evasion behavior detection method and system based on infrared thermal imaging
  • Subway fare evasion behavior detection method and system based on infrared thermal imaging
  • Subway fare evasion behavior detection method and system based on infrared thermal imaging

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Experimental program
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Effect test

Embodiment 1

[0092] see Figure II , the subway escape behavior detection method based on infrared thermal imaging, the specific operation steps are as follows:

[0093] Step S1, pedestrian detection based on deep learning: CNN extracts image features, SVM classifies the features, and detects whether pedestrians enter the pedestrian detection range of the gate image;

[0094] Step S2, using the automatically updated background to perform the background difference of the infrared thermal imaging image, and extract the overhead view image of the infrared thermal imaging of pedestrians;

[0095] Step S3, performing morphological processing on the extracted pedestrian infrared thermal imaging overhead view image to obtain a binarized overhead view image of pedestrians passing through the gate based on an automatically updated appropriate threshold;

[0096] Step S4: Perform parallel ROI extraction on the binarized pedestrian overhead view image, set the ROI area to be the same as the number N ...

Embodiment 2

[0100] This embodiment is basically the same as Embodiment 1, and the special features are as follows:

[0101] In the step S4, the parallel ROI feature region extraction is used to perform independent detection for each gate, and under the condition of reducing the calculation burden, the N gate passages are divided, and the pedestrian image processing and detection are performed independently.

[0102] In the step S6, two kinds of fare evasion judgments are carried out to N different areas, that is, N turnstile exits at the same time:

[0103] a. Detect whether someone is facing up or leaning in parallel to evade fares;

[0104] b. Detect whether someone squats or crawls to pass under the subway or across the upper part of the subway.

[0105] Said fare evasion determination a method step comprises:

[0106] Let the center of the connected area of ​​the pedestrian binary image be For an m×n binary image, use the following formula to find the center position of the object...

Embodiment 3

[0129] This subway escape detection system based on infrared thermal imaging is used for the above method, and is characterized in that: an image acquisition module (1) is connected to a voice alarm module (3) through an image processing module (2) and a fare evasion judgment module (3). 4);

[0130] The image collection module: used to collect pedestrian thermal imaging top view

[0131] The image processing module: used to extract pedestrian binary connected domain distance and area change

[0132] The fare evasion judgment module: perform parallel fare evasion and squatting / straddling fare evasion judgments

[0133] The voice alarm module: used for voice prompting of fare evasion behaviors of pedestrians and staff.

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Abstract

The invention discloses a subway fare evasion behavior detection method and system based on infrared thermal imaging. The method comprises the following steps: detecting whether a pedestrian enters agate image pedestrian detection range or not; performing infrared thermal imaging image background difference by utilizing the automatically updated background, and extracting a pedestrian infrared thermal imaging top view image; carrying out morphological processing on the extracted pedestrian infrared thermal imaging top view image to obtain a binarized pedestrian top view image passing througha gate opening based on automatic updating of an appropriate threshold value; performing parallel ROI (Region Of Interest) extraction on the binarized pedestrian top view image, and setting the ROI tobe the same as gate ports in number (N) to obtain N mutually independent binarized gate passage pedestrian top views; carrying out connected region marking on the N mutually independent binary gate passage pedestrian top view binary images to acquire pedestrian parameters; and judging fare evasion behaviors of the N gate ports. According to the invention, fare evasion behaviors can be effectivelyidentified and avoided.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method and system for detecting subway fare evasion behavior based on infrared thermal imaging. Background technique [0002] There are many solutions for traditional behavior detection, but they are limited by some objective factors, such as people wearing masks or wearing clothes of various colors to camouflage, fat and thin, high and low, carrying large bags, and objects blocking or hindering normal ordinary monocular cameras from viewing images. Normal processing, it is not easy to detect whether a person with a luggage backpack is evading fare with an ordinary camera. If the clothes are the same as the surrounding environment and the person is masked, it is difficult to detect someone tailing or squatting to evade fare. [0003] In short, ordinary cameras have a high rate of false alarms or it is difficult to immediately and accurately determine whethe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/38G06K9/32G06T7/136G06T7/187G06T7/194
CPCG06T7/136G06T7/187G06T7/194G06T2207/10016G06T2207/20104G06T2207/30232G06V40/10G06V10/28G06V10/25Y02T10/40
Inventor 高新闻李帅青简明胡珉
Owner SHANGHAI UNIV
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