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River region intrusion detection method and system and storage medium

A technology of regional intrusion and detection methods, applied in neural learning methods, electrical transmission signal systems, biological neural network models, etc. Fitting problems, reduced probability of false positives, generalization and effects of strong accuracy

Pending Publication Date: 2022-03-08
中科计算技术西部研究院
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, the monitoring of abnormal conditions in the river area is still in the manual patrol and active reminder stage of the park staff. Therefore, there are always problems such as low inspection efficiency, failure to detect dangers in time, and there are also problems such as large municipal investment and complicated personnel management.

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  • River region intrusion detection method and system and storage medium
  • River region intrusion detection method and system and storage medium
  • River region intrusion detection method and system and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0044] A method for intrusion detection in a river area, such as Figure 1-4 The following steps are shown:

[0045] S1: Data set sorting, collecting river channel images of many river monitoring areas, angles, and lighting backgrounds, adding noise images such as multi-size cropping, different gain multiples, and mosaic occlusion; and classifying the data sets; making the model generalization ability stronger, This will effectively reduce the possibility that the confidence of the target category will fluctuate between high and low;

[0046] S2: Train the 2D target detection model, build the function of the detection model, then change the traditional YOLOv5 network structure, add the operation method of removing the anchor frame and add the network test image to make the target detection model stable, and finally output the model file;

[0047] S3: Input the image for real-time inference of the 2D target detection model, output the RTSP video stream through the network came...

Embodiment 2

[0073] This embodiment provides a method for intrusion detection in a river area, please refer to Figure 5 , including the following steps:

[0074] S501. Collect video images in real time in the associated area of ​​the river course to be measured.

[0075] S502. Acquire an image frame to be tested based on the video image, and input it into the river intrusion detection model.

[0076] S503. Determine whether there is river intrusion based on the output result, if yes, go to step S504; if no, end.

[0077] S504. Determine the type of intrusion and give an early warning.

[0078] Among them, the river intrusion detection model is constructed in the following way:

[0079] Collect images in the associated area of ​​the river, perform image expansion based on the collected images to obtain noise images, and form a river image dataset based on the collected images and the expanded noise images;

[0080] Marking the river intrusion type of each image in the river image data ...

Embodiment 3

[0092] This embodiment provides a river area intrusion detection system, please refer to Figure 6 , the river area intrusion detection system includes:

[0093] Image acquisition module 61, for real-time acquisition of video images in the associated area of ​​the river to be measured;

[0094] The online monitoring module 62 communicates with the image acquisition module, and obtains the image frame to be tested based on the video image collected by the image acquisition module, inputs the river intrusion detection model, judges whether there is a river intrusion based on the output result, and determines whether there is a river intrusion. , determine the type of intrusion, generate a corresponding control signal based on the type of intrusion, and send it to the early warning module;

[0095] The early warning module 63 is communicatively connected with the online monitoring module, and is used for receiving the control signal sent by the online monitoring module, and perf...

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Abstract

The invention discloses a river region intrusion detection method and system and a storage medium, and relates to the technical field of video monitoring. The detection method comprises the following steps of collecting a video image in a to-be-detected river channel associated area in real time, obtaining a to-be-detected image frame based on the video image, inputting the to-be-detected image frame into a river channel intrusion detection model, judging whether river channel intrusion exists or not based on an output result, and determining an intrusion type and performing early warning when judging that the river channel intrusion exists. According to the river region intrusion detection method, the river intrusion data set is accurately classified, the false detection probability between model categories can be greatly reduced, it is ensured that the model can output an accurate intrusion classification target, a new hard-switch loss function is adopted, the problem of deep network overfitting can be solved, the whole function image is more smooth theoretically, and the accuracy of intrusion detection is improved. And the features are allowed to go deep into the neural network, so that the model is eventually generalized and has higher accuracy.

Description

technical field [0001] The invention relates to the technical field of video monitoring, in particular to a method for detecting intrusion in a river channel area. Background technique [0002] With the urban planning and construction of ecological protection and livable ecological living environment, the number of artificial lakes, reservoirs and lakes in the parks for people's leisure and entertainment in the city is increasing. Failure to effectively use monitoring, etc., resulting in frequent security incidents. Therefore, how to detect possible dangerous situations in time, carry out timely warnings, and reduce the occurrence of dangerous situations is of vital significance to ensure the safety of people's lives. [0003] At present, the monitoring of abnormal conditions in the river area is still at the stage of manual patrols and active reminders by the park staff. Therefore, there are always problems such as low inspection efficiency, failure to detect dangers in ti...

Claims

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Application Information

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IPC IPC(8): G06V20/40G08B13/196G06V10/774G06V10/764G06N3/08G06V10/82G06V20/52G08B7/06
CPCG08B13/19602G06N3/08G08B7/06G06F18/214G06F18/241
Inventor 李浩澜陈首信段勃杨东鑫谭光明王佩
Owner 中科计算技术西部研究院