CN112613449A - Safety helmet wearing detection and identification method and system based on video face image - Google Patents
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Abstract
The utility model discloses a safety helmet wearing detection and identification method and system based on video face images, which comprises the following steps: collecting personnel videos; dividing the collected personnel video into frames to obtain images of each frame; extracting a head region image from each frame image; extracting head region image features from the head region image; and identifying whether the person wears the safety helmet or not according to the image characteristics of the head area. The video acquisition is carried out on the person, the acquired video is analyzed, and whether the person wears the safety helmet or not is judged.
Description
Technical Field
The invention relates to the technical field of electric power capital construction safety production, in particular to a safety helmet wearing detection and identification method and system based on video face images.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The difficulty of the field environment and personnel management of the transformer substation is large, and a plurality of problems exist, such as: the problems to be solved are that the safety control strength of personnel behaviors and environmental risks needs to be increased, and the early warning is mainly carried out on abnormal behaviors such as personnel identity recognition, regional intrusion, safety helmet not wearing and the like and environmental hidden dangers such as smoke generation, fire generation and the like in a substation equipment area.
The wearing of the safety helmet is a basic requirement of electric power operation safety, in order to ensure the safety of operators and enhance the safety consciousness, transformer substation operation safety management regulations are regulated, and when the operators carry out live-line work such as transformer substation tests, overhaul and transformation, the safety helmet is worn according to the specified requirements. At present, whether a worker wears a safety helmet or not is mainly supervised by adopting on-site manual monitoring, and after an operator enters a transformer substation, the worker correctly wears the safety helmet is an important safety production measure.
Disclosure of Invention
The safety helmet wearing detection and identification method and system based on the video face images can greatly reduce the working pressure of field safety inspectors and monitoring operators on duty and improve the efficiency of field checking against regulations by acquiring the videos of the personnel, analyzing the videos, judging whether the personnel wear the safety helmet or not, and carrying out picture grabbing and video recording and carrying out voice broadcast alarm when the personnel do not wear the safety helmet.
In order to achieve the purpose, the following technical scheme is adopted in the disclosure:
in a first aspect, a method for detecting and identifying wearing of a safety helmet based on a video face image is provided, which includes:
collecting personnel videos;
dividing the collected personnel video into frames to obtain images of each frame;
extracting a head region image from each frame image;
extracting head region image features from the head region image;
and identifying whether the person wears the safety helmet or not according to the image characteristics of the head area.
Further, the specific process of extracting the head region image from each frame image is as follows:
extracting a person image from each frame image, determining a head region according to the person image, and extracting a head region image from each frame image according to the determined head region.
Further, human body features are extracted from each frame of image, and the person image is extracted from each frame of image according to the human body features.
Further, a head region is identified from the person image using a sliding window method and an AdaBoot detector.
Furthermore, the head region image features are analyzed by using a support vector machine to identify whether the person wears a safety helmet or not.
Further, color features, texture features and shape features are extracted from the head region image, and the color features, the texture features and the shape features are fused to obtain head region image features.
Further, when a certain frame of image is analyzed and the person is judged not to wear the safety helmet, the frame of image is recorded; when the frame images with the continuously set number are analyzed and all the personnel are judged not to wear the safety helmet, an alarm is given out.
In a second aspect, a safety helmet wearing detection and recognition system based on video face images is provided, which includes:
the video acquisition module is used for acquiring personnel videos;
the frame dividing module is used for dividing the collected personnel video into frames to obtain images of each frame;
the head area image extraction module is used for extracting a head area image from each frame of image;
the head region image feature extraction module is used for extracting the head region image features from the head region image;
and the safety helmet identification module is used for identifying whether the person wears the safety helmet or not according to the head region image characteristics.
In a third aspect, an electronic device is provided, which includes a memory, a processor, and computer instructions stored in the memory and executed on the processor, where the computer instructions, when executed by the processor, perform the steps of a method for detecting and identifying wearing of a safety helmet based on a video face image.
In a fourth aspect, a computer-readable storage medium is provided for storing computer instructions, which when executed by a processor, perform the steps of a method for detecting and identifying wearing of a safety helmet based on video face images.
Compared with the prior art, the beneficial effect of this disclosure is:
1. this openly can be through gathering personnel's video and carrying out the analysis to the video, judge whether personnel wear the safety helmet, reduced on-the-spot safety inspection personnel and control personnel on duty working pressure, improve the efficiency that the on-the-spot check was violating the regulations.
2. According to the safety helmet, when a person is found not to wear the safety helmet, an alarm is given, so that the person is reminded to wear the safety helmet, and the safety of the person is guaranteed.
3. According to the method and the device, the continuous frames are analyzed, when the fact that the personnel do not wear the safety helmet is known through analyzing the continuous frame images, an alarm is sent out, the result that whether the personnel wear the safety helmet or not is obtained through analyzing the continuous frames, and the accuracy of judging whether the personnel wear the safety helmet or not is improved.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
FIG. 1 is a flow chart of a method disclosed in example 1 of the present disclosure;
fig. 2 is a foreground detection image disclosed in embodiment 1 of the present disclosure;
fig. 3 is a human body region positioning image disclosed in embodiment 1 of the present disclosure;
fig. 4 is a diagram showing the result of identifying whether a person wears a hard hat according to embodiment 1 of the present disclosure.
The specific implementation mode is as follows:
the present disclosure is further described with reference to the following drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
In the present disclosure, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only relational terms determined for convenience in describing structural relationships of the parts or elements of the present disclosure, and do not refer to any parts or elements of the present disclosure, and are not to be construed as limiting the present disclosure.
In the present disclosure, terms such as "fixedly connected", "connected", and the like are to be understood in a broad sense, and mean either a fixed connection or an integrally connected or detachable connection; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present disclosure can be determined on a case-by-case basis by persons skilled in the relevant art or technicians, and are not to be construed as limitations of the present disclosure.
Example 1
The embodiment discloses a safety helmet wearing detection and identification method based on video face images, which comprises the following steps:
collecting personnel videos;
dividing the collected personnel video into frames to obtain images of each frame;
extracting a head region image from each frame image;
extracting head region image features from the head region image;
and identifying whether the person wears the safety helmet or not according to the image characteristics of the head area.
A method for detecting and identifying wearing of a safety helmet based on video face images is described in detail with reference to fig. 1 to 4.
The method comprises the steps that video acquisition devices are arranged in an operation area and an entrance and exit, the video acquisition devices adopted in the embodiment are cameras, videos of a monitored scene are acquired through the cameras, a human face detection algorithm is adopted in a video stream to obtain head area images of personnel, corresponding personnel positions, shooting time and other information are recorded, the current head area images of the personnel are compared with stored data in a database, the personnel in the scene are automatically positioned, and whether the personnel wear a safety helmet or not is further judged, if the personnel not wearing the safety helmet are detected, the system records the current frame images and gives an alarm.
The method comprises the steps of acquiring a face image of a worker in advance by using a camera or forming the face image by using a picture of the worker, processing the face image to generate a face database, and using the face database as a basis for identifying the worker.
The method comprises the steps of obtaining a person video image of a monitoring scene through a video acquisition device arranged in an operation area and an entrance and exit, obtaining a face image by adopting a face detection algorithm, and recording the position of the person and the time when the person is located at the position.
The method comprises the steps of comparing a face image extracted from a video image acquired on site with a face image in a face database, realizing identity recognition of personnel, tracking the personnel on the basis of the identity recognition of the personnel, automatically recognizing moving targets (people, vehicles and the like) in a large-picture scene through a global camera and a panoramic camera deployed at a station end, analyzing and recognizing the recognized moving targets under the condition of not losing a large-picture scene video, and taking helmet wearing recognition as an example for detailed description.
The safety helmet detection and identification mainly has the function of automatically positioning workers in a scene and further judging whether the workers wear the safety helmet, and if the workers who do not wear the safety helmet are detected, the system records the current frame image and sends an alarm. The safety helmet detection and identification mainly comprises six parts, namely video acquisition, foreground separation, human body detection, head region positioning, head region safety helmet detection, and early warning and recording of unworn safety personnel.
In the embodiment, collected video images of people are divided into frames, a head area image is extracted from each frame image, when the head area image is extracted, firstly, a Gaussian mixture (MOG or MOG2) model models background information in a monitored scene, and a moving foreground object is separated from the scene, as shown in fig. 2, the moving foreground object is a person, and meanwhile, the influence of environmental changes such as noise, shadow and the like is reduced as much as possible, and the detection result of the model provides approximate human body detection search area information for human body detection, so that the subsequent human body detection efficiency is improved and the false detection rate is reduced.
On the basis of foreground detection, whether a human body exists in the current frame image is judged and a human body area is positioned, when a human body is detected, personnel images are extracted from each frame image, and the head area of the human body is determined through the personnel images.
The specific process of determining the human head area in each frame of image is as follows: the method comprises the steps of extracting LUV color features, gradient histogram HOG features and human body shape features from each frame of image, fusing the LUV color features, the gradient histogram HOG features and the human body shape features to obtain human body features, extracting personnel images from each frame of image according to the extracted human body features, searching the personnel images by using AdaBoost and a sliding window method, and further locating human body regions.
The human body shape features are obtained by inputting the foreground images into a trained convolutional neural network for extraction.
Human body detection with different scales can be realized by combining a pyramid method. Under the framework, detection of different parts of a human body can be realized by training the AdaBoot detector on different training data and human body marking data, and fig. 3 shows the detection result of the upper half of the human body.
Because the relative position of the head region and the human body part is fixed, the head region can be obtained on the result of human body detection and positioning. The head region width and height are defined as 1/3 for the body region width, which is relative to the body as shown by the box at the head position in fig. 3.
After the head area is determined, firstly, intercepting a head area image from each frame image of the video and normalizing the head area image; secondly, extracting head region image features from the head region image, wherein the head region image features comprise color, texture and shape features of the head region, and the color, texture and shape features of the head region are fused to obtain the head region image features; and finally, identifying the extracted image characteristics of the head region by using a Support Vector Machine (SVM), and judging whether the person wears the safety helmet or not. As shown in fig. 4, a judgment result is shown, wherein if the head area is blue, it indicates that wearing of the helmet is detected, and red indicates that wearing of the helmet is not detected.
When the fact that the person does not wear the safety helmet is continuously detected, the continuously detected images are recorded, and a voice alarm is sent out to remind the person to wear the safety helmet.
In this embodiment, if 10 consecutive images (about 0.5s) are detected as the non-wearing of the helmet, the current frame image is recorded and saved (for future reference) and an alarm sound is sounded.
This openly can be through gathering personnel's video and carrying out the analysis to the video, judge whether personnel wear the safety helmet, reduced on-the-spot safety inspection personnel and control personnel on duty working pressure, improve the efficiency that the on-the-spot check was violating the regulations.
According to the safety helmet, when a person is found not to wear the safety helmet, an alarm is given, so that the person is reminded to wear the safety helmet, and the safety of the person is guaranteed.
According to the method and the device, through analyzing the continuous frames, when the fact that the person does not wear the safety helmet is obtained through analyzing the continuous frame images, an alarm is sent out, and through analyzing the continuous frames, the result that whether the person wears the safety helmet or not is obtained, and the accuracy of judging whether the person wears the safety helmet or not is improved.
Example 2
In this embodiment, a safety helmet wearing detection and recognition system based on video face images is disclosed, which includes:
the video acquisition module is used for acquiring personnel videos;
the frame dividing module is used for dividing the collected personnel video into frames to obtain images of each frame;
the head area image extraction module is used for extracting a head area image from each frame of image;
the head region image feature extraction module is used for extracting the head region image features from the head region image;
and the safety helmet identification module is used for identifying whether the person wears the safety helmet or not according to the head region image characteristics.
Example 3
In this embodiment, an electronic device is disclosed, which includes a memory, a processor and computer instructions stored in the memory and executed on the processor, where the computer instructions, when executed by the processor, implement the steps of the method for detecting and identifying the wearing of a safety helmet based on a video face image disclosed in embodiment 1.
Example 4
In this embodiment, a computer readable storage medium is disclosed for storing computer instructions, which when executed by a processor, perform the steps of the method for detecting and identifying the wearing of a safety helmet based on a video face image disclosed in embodiment 1.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A safety helmet wearing detection and identification method based on video face images is characterized by comprising the following steps:
collecting personnel videos;
dividing the collected personnel video into frames to obtain images of each frame;
extracting a head region image from each frame image;
extracting head region image features from the head region image;
and identifying whether the person wears the safety helmet or not according to the image characteristics of the head area.
2. The method for detecting and identifying wearing of safety helmet based on video human face image as claimed in claim 1, wherein the specific process of extracting the image of head region from each frame of image is as follows:
extracting a person image from each frame image, determining a head region according to the person image, and extracting a head region image from each frame image according to the determined head region.
3. The method as claimed in claim 2, wherein the human body features are extracted from each frame of image, and the person image is extracted from each frame of image according to the human body features.
4. The method for detecting and identifying wearing of safety helmets based on video face images as claimed in claim 2, wherein the head region is identified from the images of the person by using a sliding window method and an AdaBoot detector.
5. The method for detecting and identifying wearing of safety helmets based on video face images as claimed in claim 1, wherein a support vector machine is used to analyze the image characteristics of the head region to identify whether a person wears a safety helmet.
6. The method for detecting and identifying wearing of safety helmet based on video human face image as claimed in claim 1, wherein color feature, texture feature and shape feature are extracted from the head region image, and the color feature, texture feature and shape feature are fused to obtain the head region image feature.
7. The method for detecting and identifying wearing of safety helmet based on video human face image as claimed in claim 1, wherein when analyzing a certain frame of image and determining that the person does not wear the safety helmet, recording the frame of image; when the frame images with the continuously set number are analyzed and all the personnel are judged not to wear the safety helmet, an alarm is given out.
8. A safety helmet wearing detection and recognition system based on video face images is characterized by comprising:
the video acquisition module is used for acquiring personnel videos;
the frame dividing module is used for dividing the collected personnel video into frames to obtain images of each frame;
the head area image extraction module is used for extracting a head area image from each frame of image;
the head region image feature extraction module is used for extracting the head region image features from the head region image;
and the safety helmet identification module is used for identifying whether the person wears the safety helmet or not according to the head region image characteristics.
9. An electronic device comprising a memory and a processor, and computer instructions stored on the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the steps of a method for video face image based headgear wear detection and identification of any of claims 1-7.
10. A computer readable storage medium storing computer instructions which, when executed by a processor, perform the steps of the method for detecting and identifying wearing of a helmet based on video face images according to any one of claims 1 to 7.
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| CN111368746A (en) * | 2020-03-06 | 2020-07-03 | 杭州宇泛智能科技有限公司 | Method and device for detecting wearing state of personal safety helmet in video and electronic equipment |
| CN111414825A (en) * | 2020-03-13 | 2020-07-14 | 玉林师范学院 | Wearing detection method for safety helmet |
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| CN113221783A (en) * | 2021-05-20 | 2021-08-06 | 上海可深信息科技有限公司 | Low-resolution image helmet identification method |
| CN113469043A (en) * | 2021-06-30 | 2021-10-01 | 南方科技大学 | Method and device for detecting wearing state of safety helmet, computer equipment and storage medium |
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