CN118279834A - Intelligent safety monitoring system based on visual identification - Google Patents
Intelligent safety monitoring system based on visual identification Download PDFInfo
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Abstract
The invention discloses an intelligent safety monitoring system based on visual identification, which belongs to the technical field of visual identification and comprises a data acquisition module, a data preprocessing module, an intelligent identification analysis module, a decision response module, a video storage module and an interactive interface.
Description
Technical Field
The invention belongs to the technical field of visual identification, and particularly relates to an intelligent safety monitoring system based on visual identification.
Background
With rapid development of technology, the field of safety monitoring is gradually changed from the traditional manual monitoring to an intelligent and automatic monitoring mode;
However, the existing visual recognition intelligent security monitoring system has certain defects, the existing visual recognition intelligent security monitoring system lacks all-weather uninterrupted monitoring capability, so that data at certain key moments are lost, a bottleneck may exist in a data processing flow, delay from data acquisition to analysis is long, rapid response to sudden events is affected, accuracy and depth in terms of object detection, feature extraction recognition and behavior analysis may be insufficient, the system is difficult to accurately distinguish different types of objects and inaccurate in positioning, or deviation occurs in complex behavior pattern recognition, an effective data pretreatment mechanism is lacking, such as incompatible formats, unsuitable resolutions, a large amount of noise, color distortion and the like exist in videos, the quality of data received by an intelligent analysis module is low, the existing system may need manual intervention to analyze an alarm, judge the situation and respond when the existing system faces security threats, the process is time-consuming and low in efficiency, a decision response mechanism is not flexible and intelligent enough, and the alarm cannot be triggered automatically, so that the probability of false alarm and missing is increased, and the intelligent security monitoring system based on visual recognition is provided.
Disclosure of Invention
The invention aims to provide an intelligent safety monitoring system based on visual identification so as to solve the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: an intelligent safety monitoring system based on visual recognition comprises a data acquisition module, a data preprocessing module, an intelligent recognition analysis module, a decision response module, a video storage module and an interactive interface;
the data acquisition module is responsible for capturing video data from a monitoring site, acquiring the video data of a monitoring area in all weather through a high-definition camera network, and providing original data input for the whole monitoring system;
The data preprocessing module performs preliminary processing on the collected original video data, and comprises format conversion, resolution adjustment, noise removal and color correction preprocessing operations;
the intelligent recognition analysis module automatically recognizes and analyzes video content according to the processed data and predicts events;
When abnormal behaviors are detected, the decision response module automatically triggers an alarm system, sends instant notification to related devices and controls field devices;
the video storage module is used for storing the processed data and performing interactive operation with the interactive interface;
The interactive interface receives video data of the video storage module and alarm information of the decision response module.
The data acquisition module is connected with the equipment, a data transmission path is configured, data is set and transmitted from the acquisition module to a final storage processing place, equipment data is acquired in real time, all-weather uninterrupted video data acquisition is realized through a high-definition camera network, and the high-efficiency streaming processing technology is combined, so that real-time coverage of a monitoring area is ensured, delay of data processing is reduced, and response speed to an emergency is improved.
The data preprocessing module performs preliminary processing on the acquired original video data, wherein the preliminary processing comprises format conversion, resolution adjustment, noise removal and color correction preprocessing operation, and the video data source of the data acquisition module is received to perform format conversion;
the format conversion implementation formula is:
In the formula, C (u, v) is expressed as a transformed coefficient, the coefficient of the position u, v in the frequency domain, C (x, y) is expressed as an original pixel value, N is expressed as half the image size, x, y is expressed as row and column coordinates in the spatial domain;
After format conversion, image enhancement is carried out, and the realization formula is as follows:
Ieq(x,y)＝S(I(x,y))，
In the formula, I eq represents the gray value of the pixel at the coordinates (x, y) in the equalized image, and I (x, y) represents the gray value of the pixel at (x, y).
The intelligent recognition analysis module is used for carrying out object detection, feature extraction recognition and behavior analysis;
The object detection reads images from a video stream, performs necessary preprocessing on each frame of images, inputs the preprocessed images into a model, outputs a series of bounding boxes and corresponding class probabilities by the model, screens a prediction result according to a threshold value, removes a detection box with low confidence, applies algorithms such as non-maximum suppression and the like to remove an overlapped frame, and finally determines a target object and the position of the target object in each frame, wherein the implementation formula is as follows:
in the formula, S 2 represents the number of grids, B represents a convenient frame book of grid prediction, and lambda coord represents a weight factor The indication function is represented by a representation of the indication function,And, a step of, in the first embodiment,Representing the actual and predicted bounding box center coordinates.
The intelligent recognition analysis module integrates object detection, feature extraction recognition and behavior analysis functions, not only can accurately recognize various objects and positions thereof in a monitoring picture, but also can deeply analyze behavior modes thereof, thereby effectively improving early warning precision and judgment capability of the system and reducing false alarm rate.
The feature extraction and recognition method comprises the steps of cutting out each target object from original images according to object detection results, processing the cut-out images by using a feature extraction model to obtain feature vectors, inputting the feature vectors into a pre-trained classification model, and carrying out accurate category recognition of the targets;
The behavior analysis tracks the same object in continuous frames, builds a motion track, analyzes an action sequence of the object based on track data, recognizes a specific behavior mode through a model by calculating speed and direction change characteristics, sets a time window and analyzes behavior change of the object in the window.
The decision response module matches the information with preset safety rules according to the information of the type, the behavior, the position and the like of the object detected by the intelligent recognition analysis module, evaluates whether an alarm condition is triggered or not, once the analysis result shows that safety threat exists, the system immediately generates alarm information, automatically sends a short message containing the information of alarm content, the position and the like to preset safety personnel, sends a detailed alarm report to a mailbox of related personnel, classifies the alarm according to the threat degree, starts an emergency plan in emergency, and automatically sends instructions to related safety equipment according to preset logic.
The video storage module receives the video data stream from the data preprocessing module, adopts a stream processing technology, stores the video data stream while receiving, distributes a storage path and a file name for the video data stream according to a storage strategy, temporarily stores video fragments by using a cache technology, writes the video fragments into cloud storage in batch in real time, and performs data verification in the storage process.
Compared with the prior art, the invention has the beneficial effects that:
1. The invention realizes all-weather uninterrupted video data acquisition through the high-definition camera network, and combines the high-efficiency streaming processing technology, thereby ensuring the real-time coverage of a monitoring area, reducing the delay of data processing and improving the response speed to an emergency;
2. According to the invention, the intelligent recognition analysis module integrates object detection, feature extraction recognition and behavior analysis functions, so that not only can various objects and positions thereof in a monitoring picture be accurately recognized, but also behavior modes thereof can be deeply analyzed, thereby effectively improving early warning precision and judgment capability of the system and reducing false alarm rate;
3. According to the invention, the data preprocessing module is used for executing multidimensional video optimization, including format conversion, resolution adjustment, noise removal, color correction and the like, so that the quality of video data is obviously improved, a clearer and more accurate input source is provided for subsequent intelligent analysis, and meanwhile, the use of storage resources is optimized;
4. the invention can quickly take action according to the analysis result by the decision response module, automatically trigger alarm, send notification and control the field device to form a closed-loop safety response system, thereby greatly shortening the time from the discovery of abnormality to the taking of measures and enhancing the coping efficiency of safety events.
Drawings
FIG. 1 is a schematic diagram of an intelligent security monitoring system based on visual recognition;
FIG. 2 is a flow chart of operation of an intelligent security monitoring system based on visual identification according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
Referring to fig. 1-2, the present invention provides a technical solution: the intelligent recognition system comprises a data acquisition module, a data preprocessing module, an intelligent recognition analysis module, a decision response module, a video storage module and an interactive interface;
the data acquisition module is responsible for capturing video data from a monitoring site, acquiring the video data of a monitoring area in all weather through a high-definition camera network, and providing original data input for the whole monitoring system;
The data preprocessing module performs preliminary processing on the collected original video data, and comprises format conversion, resolution adjustment, noise removal and color correction preprocessing operations;
the intelligent recognition analysis module automatically recognizes and analyzes video content according to the processed data and predicts events;
When abnormal behaviors are detected, the decision response module automatically triggers an alarm system, sends instant notification to related devices and controls field devices;
the video storage module is used for storing the processed data and performing interactive operation with the interactive interface;
The interactive interface receives video data of the video storage module and alarm information of the decision response module.
The data acquisition module is connected with the equipment, a data transmission path is configured, data is set and transmitted from the acquisition module to a final storage processing place, equipment data is acquired in real time, all-weather uninterrupted video data acquisition is realized through a high-definition camera network, and the high-efficiency streaming processing technology is combined, so that real-time coverage of a monitoring area is ensured, delay of data processing is reduced, and response speed to an emergency is improved.
The data preprocessing module performs preliminary processing on the acquired original video data, wherein the preliminary processing comprises format conversion, resolution adjustment, noise removal and color correction preprocessing operation, and the video data source of the data acquisition module is received to perform format conversion;
the format conversion implementation formula is:
In the formula, C (u, v) is expressed as a transformed coefficient, the coefficient of the position u, v in the frequency domain, C (x, y) is expressed as an original pixel value, N is expressed as half the image size, x, y is expressed as row and column coordinates in the spatial domain;
After format conversion, image enhancement is carried out, and the realization formula is as follows:
Ieq(x,y)＝S(I(x,y))，
In the formula, I eq represents the gray value of the pixel at the coordinates (x, y) in the equalized image, and I (x, y) represents the gray value of the pixel at (x, y).
The intelligent recognition analysis module is used for carrying out object detection, feature extraction recognition and behavior analysis;
The object detection reads images from a video stream, performs necessary preprocessing on each frame of images, inputs the preprocessed images into a model, outputs a series of bounding boxes and corresponding class probabilities by the model, screens a prediction result according to a threshold value, removes a detection box with low confidence, applies algorithms such as non-maximum suppression and the like to remove an overlapped frame, and finally determines a target object and the position of the target object in each frame, wherein the implementation formula is as follows:
in the formula, S 2 represents the number of grids, B represents a convenient frame book of grid prediction, and lambda coord represents a weight factor The indication function is represented by a representation of the indication function,And, a step of, in the first embodiment,Representing the actual and predicted bounding box center coordinates.
The intelligent recognition analysis module integrates object detection, feature extraction recognition and behavior analysis functions, not only can accurately recognize various objects and positions thereof in a monitoring picture, but also can deeply analyze behavior modes thereof, thereby effectively improving early warning precision and judgment capability of the system and reducing false alarm rate.
The feature extraction and recognition method comprises the steps of cutting out each target object from original images according to object detection results, processing the cut-out images by using a feature extraction model to obtain feature vectors, inputting the feature vectors into a pre-trained classification model, and carrying out accurate category recognition of the targets;
The behavior analysis tracks the same object in continuous frames, builds a motion track, analyzes an action sequence of the object based on track data, recognizes a specific behavior mode through a model by calculating speed and direction change characteristics, sets a time window and analyzes behavior change of the object in the window.
The decision response module matches the information with preset safety rules according to the information of the type, the behavior, the position and the like of the object detected by the intelligent recognition analysis module, evaluates whether an alarm condition is triggered or not, once the analysis result shows that safety threat exists, the system immediately generates alarm information, automatically sends a short message containing the information of alarm content, the position and the like to preset safety personnel, sends a detailed alarm report to a mailbox of related personnel, classifies the alarm according to the threat degree, starts an emergency plan in emergency, and automatically sends instructions to related safety equipment according to preset logic.
The video storage module receives the video data stream from the data preprocessing module, adopts a stream processing technology, stores the video data stream while receiving, distributes a storage path and a file name for the video data stream according to a storage strategy, temporarily stores video fragments by using a cache technology, writes the video fragments into cloud storage in batch in real time, and performs data verification in the storage process.
In this example, specific: the data preprocessing module performs preliminary processing on the acquired original video data, including format conversion, resolution adjustment, noise removal and color correction preprocessing operation, and the video data source of the data acquisition module is received to perform format conversion;
the format conversion implementation formula is:
In the formula, C (u, v) is expressed as a transformed coefficient, the coefficient of the position u, v in the frequency domain, C (x, y) is expressed as an original pixel value, N is expressed as half the image size, x, y is expressed as row and column coordinates in the spatial domain;
After format conversion, image enhancement is carried out, and the realization formula is as follows:
Ieq(x,y)＝S(I(x,y))，
In the formula, I eq represents the gray value of the pixel at the coordinates (x, y) in the equalized image, and I (x, y) represents the gray value of the pixel at (x, y).
In this example, specific: the intelligent recognition analysis module performs object detection, feature extraction recognition and behavior analysis;
The object detection reads images from a video stream, performs necessary preprocessing on each frame of images, inputs the preprocessed images into a model, outputs a series of bounding boxes and corresponding class probabilities by the model, screens a prediction result according to a threshold value, removes a detection box with low confidence, applies algorithms such as non-maximum suppression and the like to remove an overlapped frame, and finally determines a target object and the position of the target object in each frame, wherein the implementation formula is as follows:
in the formula, S 2 represents the number of grids, B represents a convenient frame book of grid prediction, and lambda coord represents a weight factor The indication function is represented by a representation of the indication function,And, a step of, in the first embodiment,Representing the actual and predicted bounding box center coordinates.
The intelligent recognition analysis module integrates object detection, feature extraction recognition and behavior analysis functions, not only can accurately recognize various objects and positions thereof in a monitoring picture, but also can deeply analyze behavior modes thereof, thereby effectively improving early warning precision and judgment capability of the system and reducing false alarm rate.
The feature extraction and recognition method comprises the steps of cutting out each target object from original images according to object detection results, processing the cut-out images by using a feature extraction model to obtain feature vectors, inputting the feature vectors into a pre-trained classification model, and carrying out accurate category recognition of the targets;
The behavior analysis tracks the same object in continuous frames, builds a motion track, analyzes an action sequence of the object based on track data, recognizes a specific behavior mode through a model by calculating speed and direction change characteristics, sets a time window and analyzes behavior change of the object in the window.
Working principle: the method comprises the steps that video data are continuously collected all weather by a high-definition camera network deployed on a monitoring site, a camera is connected with a data collection module, and received original video data firstly enter a data preprocessing module through a pre-configured data transmission path to comprise format conversion so as to adapt to the requirements of subsequent processing, adjust resolution, remove noise and improve the definition of pictures; color correction, the color of the image is enabled to be more real, the preprocessed video data are sent to an intelligent recognition analysis module, object detection is firstly carried out, a deep learning model is utilized to identify a target object and the position of the target object in each frame, a boundary frame prediction and non-maximum suppression algorithm are utilized, then, a feature extraction recognition stage carries out fine classification on the target based on detection results, a behavior analysis module tracks the motion trail of the object in continuous frames, abnormal behaviors are recognized through analysis of the motion patterns, a decision response module evaluates whether safety risks exist in the current scene or not based on the result of intelligent recognition analysis, if potential threats are detected, a system rapidly takes action, an alarm is triggered, instant notification is sent to a safety personnel, the video data after being received and processed in real time by a preset logic control field device video storage module are utilized to store the video data while receiving by a streaming processing technology, and video stream and alarm information are displayed by an interactive interface;
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations may be made therein without departing from the spirit and scope of the invention as defined by the appended claims and their equivalents.
The invention and its embodiments have been described above with no limitation, and the actual construction is not limited to the embodiments of the invention as shown in the drawings. In summary, if one of ordinary skill in the art is informed by this disclosure, a structural manner and an embodiment similar to the technical solution should not be creatively devised without departing from the gist of the present invention.
Claims (7)
1. An intelligent security monitored control system based on visual identification, its characterized in that: the intelligent recognition system comprises a data acquisition module, a data preprocessing module, an intelligent recognition analysis module, a decision response module, a video storage module and an interactive interface;
the data acquisition module is responsible for capturing video data from a monitoring site, acquiring the video data of a monitoring area in all weather through a high-definition camera network, and providing original data input for the whole monitoring system;
The data preprocessing module performs preliminary processing on the collected original video data, and comprises format conversion, resolution adjustment, noise removal and color correction preprocessing operations;
the intelligent recognition analysis module automatically recognizes and analyzes video content according to the processed data and predicts events;
When abnormal behaviors are detected, the decision response module automatically triggers an alarm system, sends instant notification to related devices and controls field devices;
the video storage module is used for storing the processed data and performing interactive operation with the interactive interface;
The interactive interface receives video data of the video storage module and alarm information of the decision response module.
2. The visual identification-based intelligent security monitoring system of claim 1, wherein: the data acquisition module is connected with the equipment to configure a data transmission path, and the set data is transmitted to a final storage processing place from the acquisition module to acquire the equipment data in real time.
3. The visual identification-based intelligent security monitoring system of claim 1, wherein: the data preprocessing module performs preliminary processing on the acquired original video data, including format conversion, resolution adjustment, noise removal and color correction preprocessing operation, and the video data source of the data acquisition module is received to perform format conversion;
the format conversion implementation formula is:
In the formula, C (u, v) is expressed as a transformed coefficient, the coefficient of the position u, v in the frequency domain, C (x, y) is expressed as an original pixel value, N is expressed as half the image size, x, y is expressed as row and column coordinates in the spatial domain;
After format conversion, image enhancement is carried out, and the realization formula is as follows:
Ieq(x,y)＝S(I(x,y))，
In the formula, I eq represents the gray value of the pixel at the coordinates (x, y) in the equalized image, and I (x, y) represents the gray value of the pixel at (x, y).
4. The visual identification-based intelligent security monitoring system of claim 1, wherein: the intelligent recognition analysis module performs object detection, feature extraction recognition and behavior analysis;
The object detection reads images from a video stream, preprocesses each frame of images, inputs the preprocessed images into a model, outputs a series of bounding boxes and corresponding class probabilities by the model, screens a prediction result according to a threshold value, removes a detection box with low confidence, applies algorithms such as non-maximum suppression and the like to remove an overlapped frame, and finally determines a target object and the position of the target object in each frame, wherein the implementation formula is as follows:
in the formula, S 2 represents the number of grids, B represents a convenient frame book of grid prediction, and lambda coord represents a weight factor The indication function is represented by a representation of the indication function,And, a step of, in the first embodiment,Representing the actual and predicted bounding box center coordinates.
5. The visual identification-based intelligent security monitoring system of claim 4, wherein: the feature extraction and recognition is carried out, according to the object detection result, each target object is cut out from the original image, the cut image is processed by using a feature extraction model, a feature vector is obtained, the feature vector is input into a pre-trained classification model, and accurate category recognition of the target is carried out;
The behavior analysis tracks the same object in continuous frames, builds a motion track, analyzes an action sequence of the object based on track data, recognizes a specific behavior mode through a model by calculating speed and direction change characteristics, sets a time window and analyzes behavior change of the object in the window.
6. The visual identification-based intelligent security monitoring system of claim 1, wherein: the decision response module is used for matching the information with preset safety rules according to the information of the type, the behavior, the position and the like of the object detected by the intelligent recognition analysis module, evaluating whether an alarm condition is triggered or not, once the analysis result shows that safety threat exists, the system immediately generates alarm information, automatically sends a short message containing the information of alarm content, the position and the like to preset safety personnel, sends a detailed alarm report to a mailbox of related personnel, classifies the alarm according to the threat degree, starts an emergency plan in emergency, and automatically sends instructions to related safety equipment according to preset logic.
7. The visual identification-based intelligent security monitoring system of claim 1, wherein: the video storage module receives the video data stream from the data preprocessing module, adopts a stream processing technology, stores the video data stream while receiving, distributes a storage path and a file name for the video data stream according to a storage strategy, temporarily stores video fragments by using a cache technology, writes the video fragments into cloud storage in batch in real time, and performs data verification in the storage process.
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