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Transformer station worker helmet wear detection method based on video analysis

A technology of video analysis and safety helmet, which is applied in the directions of instruments, calculations, character and pattern recognition, etc., can solve the problem of low efficiency of safety helmet recognition, and achieve the effect of improved recognition rate and false positive rate, and good robustness

Pending Publication Date: 2017-02-22
CHONGQING UNIV +2
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Problems solved by technology

[0004] The purpose of the present invention provides a method of helmet detection based on HSV color space features, Haar features, and Adaboost cascade classifier fusion, and t

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  • Transformer station worker helmet wear detection method based on video analysis
  • Transformer station worker helmet wear detection method based on video analysis
  • Transformer station worker helmet wear detection method based on video analysis

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Embodiment Construction

[0061] The present invention will be further described below in conjunction with embodiments, but it should not be understood that the scope of the above subject matter of the present invention is limited to the following embodiments. Without departing from the above technical idea of ​​the present invention, various substitutions and changes based on common technical knowledge and conventional means in the field should be included in the protection scope of the present invention.

[0062] A video analysis-based detection method for substation workers wearing helmets includes the following steps:

[0063] 1) Prepare positive and negative samples:

[0064] Positive sample collection: positive samples of safety helmets are normalized and contain little background, and negative samples do not contain background images of safety helmets in the substation environment; the size is unified as W×H=24×24; negative sample collection: collect actual scenes of substations The negative sample do...

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Abstract

The invention discloses a transformer station worker helmet wear detection method based on video analysis. According to the method, a VIBE algorithm is selected to detect a motion target region and an HSV color characteristic preliminary positioning helmet region on the basis of a transformer station scene, Haar characteristics and HSV color space characteristics are acquired through selection and fusion, positive and negative helmet samples under the field scene are acquired, an Adaboost algorithm is utilized to carry out classifier training, fusion characteristics of a positioning helmet region are extracted and are sent to a trained helmet classifier to carry out characteristic matching detection, and thereby precise helmet identification positioning is realized. Compared with a traditional method, the method is advantaged in that high accuracy and good robustness are realized, a worker region can be rapidly and accurately positioned whether workers wear helmets or not and whether all personnel targets appear in a camera region or not, behaviors of wearing no helmets are timely warned, and hidden safety trouble is eliminated.

Description

Technical field [0001] This invention relates to the field of intelligent video surveillance. Background technique [0002] With the frequent occurrence of safety accidents of workers in substation sites, the detection of workers’ helmets and tracking alarms are of great significance to the safe production of the power industry. An effective monitoring method must be required. For workers in substation sites, they can work without a helmet. The phenomenon was discovered and reported to the police in time. The power industry is the lifeline of economic development, and substations are an important part of power production. The country is paying more and more attention to the safety of substations, and monitoring efforts are constantly increasing. Corresponding monitoring measures have been adopted in most substation sites across the country, effectively preventing the occurrence of major safety accidents. At present, the monitoring of the wearing of helmets by workers in substat...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2148G06F18/24
Inventor 范敏吴松麟杜思远徐浩瞿雯睿韩琪刘海龙宿晓岚刘亚玲
Owner CHONGQING UNIV
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