CN110545383A - Video integrated management platform system - Google Patents
Video integrated management platform system Download PDFInfo
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- CN110545383A CN110545383A CN201910870976.7A CN201910870976A CN110545383A CN 110545383 A CN110545383 A CN 110545383A CN 201910870976 A CN201910870976 A CN 201910870976A CN 110545383 A CN110545383 A CN 110545383A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/40—Document-oriented image-based pattern recognition
- G06V30/41—Analysis of document content
- G06V30/413—Classification of content, e.g. text, photographs or tables
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/95—Computational photography systems, e.g. light-field imaging systems
- H04N23/951—Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/222—Studio circuitry; Studio devices; Studio equipment
- H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
- H04N5/2624—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects for obtaining an image which is composed of whole input images, e.g. splitscreen
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/76—Television signal recording
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Television Signal Processing For Recording (AREA)
Abstract
the invention discloses a video comprehensive management platform system, which comprises the following modules: and the acquisition module is used for acquiring data of the area of the required video. The invention has the following effects: the video is discerned the characters region when looking over, draws the editor to the figure and the characters that discern, forms the brief explanation of video, and the recognition process accuracy is high, can realize the discernment of drawing of different grade type figure and characters, and the image application scope is more extensive, and the video efficiency of looking over will promote by a wide margin. By dividing the video image frame into a plurality of data blocks and performing self-adaptive prediction on the data blocks, the characteristic values of the data blocks are extracted in the judging process and are converted into the comparison of corresponding characteristic values, so that the processing efficiency is improved, and the accurate judgment and processing of the quality of the video data are realized.
Description
Technical Field
The invention belongs to the technical field of videos, and particularly relates to a video comprehensive management platform system.
Background
With the development of economy, the popularization trend of video monitoring is more and more obvious, the monitoring area is wider and wider, the data flow is larger and larger, and how to effectively manage the video data of the monitoring system becomes a problem to be solved urgently. The existing video is taken and read one by one for human eye observation, which wastes time and labor. In addition, during processing, because a single frame image is large, sometimes the monitoring resolution is low, noise or shielding is easy to occur, the precision judgment and processing efficiency on the video data quality is very low, and the calculation speed is slow
disclosure of Invention
the invention aims to overcome the defects and provides a video integrated management platform system, which comprises the following modules:
The acquisition module is used for acquiring data of a region of a required video;
The data processing module is used for carrying out data processing on the acquired video data and then storing the video subjected to data processing into the hard disk; performing multiple sectional screenshots on each video in the hard disk to form multiple screenshots, and splicing the multiple screenshots into a visual view;
The retrieval query module is used for retrieving and querying the video data stored in the cloud platform;
and the download transmission module is used for downloading the retrieved video data and transmitting the video data to the terminal equipment of the user.
The invention has the following effects: the video is discerned the characters region when looking over, draws the editor to the figure and the characters that discern, forms the brief explanation of video, and the recognition process accuracy is high, can realize the discernment of drawing of different grade type figure and characters, and the image application scope is more extensive, and the video efficiency of looking over will promote by a wide margin. By dividing the video image frame into a plurality of data blocks and performing self-adaptive prediction on the data blocks, the characteristic values of the data blocks are extracted in the judging process and are converted into the comparison of corresponding characteristic values, so that the processing efficiency is improved, and the accurate judgment and processing of the quality of the video data are realized.
drawings
fig. 1 is a schematic diagram of the present invention.
Detailed Description
The invention is further illustrated by the following specific examples:
a video integrated management platform system comprises the following modules:
The acquisition module is used for acquiring data of a region of a required video;
The data processing module is used for carrying out data processing on the acquired video data and then storing the video subjected to data processing into the hard disk; performing multiple sectional screenshots on each video in the hard disk to form multiple screenshots, and splicing the multiple screenshots into a visual view;
The retrieval query module is used for retrieving and querying the video data stored in the cloud platform;
and the download transmission module is used for downloading the retrieved video data and transmitting the video data to the terminal equipment of the user.
the data processing module comprises an indexing module, which is used for indexing the visual views after splicing a plurality of screenshots into one visual view, carrying out image binarization on the visual views, marking character areas by using highlight polygons, carrying out digital identification on the character areas one by one, judging whether code scrambling occurs or not, filtering the identification result if the code scrambling occurs, selecting a first identification number as a reference point if the code scrambling does not occur, selecting coordinates (x1 and y1) of the reference point on the screenshots, reading the coordinates (x2 and y2) of the reference point in the visual views, selecting coordinates (x3 and y3) of a second identification number on the screenshots, calculating the coordinates (x4 and y4) in the visual views corresponding to the second identification number, wherein x4 is x2- (x3-x1) x3r, and y4 is y2- (y1-y3) x3r, and r is a unit pixel coordinate increment, comparing the difference value between the two coordinates (x3, y3) and (x4, y4), if the difference value is smaller than a set threshold value, determining that the character area identification result corresponding to the two coordinates is correct, and extracting and editing the identified numbers and characters to form a brief description of the video.
The data processing module comprises a prediction module, and is used for performing data processing on the acquired video data and then storing the video subjected to data processing into a hard disk, and the data processing module specifically comprises: dividing a video image frame into a plurality of data blocks, predicting the pixel position pn of one data block at a time, wherein pn represents the predicted position of a pixel in an nth frame, and pn-1 is the position of a final pixel in the n-1 frame; an is a state transition matrix, on is An external control vector, Bn is An external control matrix, cn is a random variable, the predicted pixel position of the data block is compared with a pre-stored reference data block, whether the noise meets the condition is judged, if not, correction is carried out, if yes, the data block which is already predicted in the video image frame is marked, and all the data blocks are traversed.
The prediction module comprises a comparison module for comparing the predicted pixel position of the data block with a pre-stored reference data block, specifically: the position feature value of the extracted prediction data block is FA ═ (i, k), and the feature value of the extracted reference data block is FB ═ (j, t). If i < j, the prediction data block is smaller than the reference data block; if i > j, the prediction data block is larger than the reference data block; if i ═ j, then continue comparing k and t: if k < t, the prediction data block is smaller than the reference data block; if k > t, the prediction data block is larger than the reference data block; if (k ═ t and k ═ i +1) or (k ═ t and i-k ═ 0), the prediction data block is equal to the reference data block; otherwise, starting from the i-k-1 th bit of the prediction data block and the j-t-1 th bit of the reference data block, re-extracting the characteristic value FA (i, k) of the prediction data block and the characteristic value FB (j, t) of the reference data block in the direction of the low bit, and then repeating the steps.
the management method of the video integrated management platform system comprises the following steps:
acquiring data of a region of a required video;
Carrying out data processing on the acquired video data, and then storing the video subjected to data processing into a hard disk;
performing multiple sectional screenshots on each video in the hard disk to form multiple screenshots, and splicing the multiple screenshots into a visual view;
Retrieving and inquiring video data stored in a cloud platform;
the retrieved video data is downloaded and transmitted to the user's terminal device.
After splicing a plurality of screenshots into a visual view, indexing the visual view, specifically comprising the following steps: performing image binarization on the visual view, marking a character area by using a highlight polygon, performing number recognition on the character area one by one, judging whether the character area is subjected to scrambling code or not, filtering a recognition result if the character area is subjected to scrambling code, selecting a first recognition number as a reference point if the character area is not subjected to scrambling code, calculating coordinates (x1 and y1) of the reference point on the screenshot, reading the coordinates (x2 and y2) of the reference point in the visual view, selecting coordinates (x3 and y3) of a second recognition number on the screenshot, calculating coordinates (x4 and y4) in the visual view corresponding to the second recognition number, wherein r is a unit pixel coordinate increment, comparing a difference value between the two coordinates (x3 and y 465) and the coordinates (x4 and y4) if the difference value is smaller than a set threshold value, and judging that the character area identification results corresponding to the two coordinates are correct, and extracting and editing the identified numbers and characters to form a brief description of the video.
The data processing of the acquired video data and the storage of the video after the data processing into the hard disk specifically comprise: dividing a video image frame into a plurality of data blocks, predicting the pixel position pn of one data block at a time, wherein pn represents the predicted position of a pixel in an nth frame, and pn-1 is the position of a final pixel in the n-1 frame; an is a state transition matrix, on is An external control vector, Bn is An external control matrix, cn is a random variable, the predicted pixel position of the data block is compared with a pre-stored reference data block, whether the noise meets the condition is judged, if not, correction is carried out, if yes, the data block which is already predicted in the video image frame is marked, and all the data blocks are traversed.
Comparing the predicted pixel position of the data block with a pre-stored reference data block specifically comprises: the position feature value of the extracted prediction data block is FA ═ (i, k), and the feature value of the extracted reference data block is FB ═ (j, t). If i < j, the prediction data block is smaller than the reference data block; if i > j, the prediction data block is larger than the reference data block; if i ═ j, then continue comparing k and t: if k < t, the prediction data block is smaller than the reference data block; if k > t, the prediction data block is larger than the reference data block; if (k ═ t and k ═ i +1) or (k ═ t and i-k ═ 0), the prediction data block is equal to the reference data block; otherwise, starting from the i-k-1 th bit of the prediction data block and the j-t-1 th bit of the reference data block, re-extracting the characteristic value FA (i, k) of the prediction data block and the characteristic value FB (j, t) of the reference data block in the direction of the low bit, and then repeating the steps.
When data acquisition is carried out on the area of the required video, a plurality of camera heads are adopted to carry out video monitoring acquisition.
And storing the video subjected to data processing into a hard disk, wherein the hard disk can be a temporarily stored mobile hard disk.
Retrieving and inquiring video data stored in the cloud platform, downloading the retrieved video data and transmitting the retrieved video data to the terminal equipment of the user, and if the user needs to call a video record within a certain period of time, retrieving the required video through any terminal connected to the network, and downloading the video to the terminal equipment for watching.
Claims (7)
1. The video integrated management platform system is characterized by comprising the following modules:
The acquisition module is used for acquiring data of a region of a required video;
the data processing module is used for carrying out data processing on the acquired video data and then storing the video subjected to data processing into the hard disk; performing multiple sectional screenshots on each video in the hard disk to form multiple screenshots, and splicing the multiple screenshots into a visual view;
The retrieval query module is used for retrieving and querying the video data stored in the cloud platform;
And the download transmission module is used for downloading the retrieved video data and transmitting the video data to the terminal equipment of the user.
2. the video integrated management platform system according to claim 1, wherein the data processing module comprises an indexing module, configured to index a plurality of screenshots into a visual view, perform image binarization on the visual view, mark text areas by using a highlight polygon, perform number recognition on the text areas one by one, determine whether a scrambling code occurs, filter a recognition result if the scrambling code occurs, select a first recognition number as a reference point if the scrambling code does not occur, select coordinates (x1, y1) of the reference point on the screenshot, read coordinates (x2, y2) of the reference point in the visual view, select coordinates (x3, y3) of a second recognition number on the screenshot, calculate coordinates (x4, y4) in the visual view corresponding to the second recognition number, x 4-x 2- (x3-x1) × 3r, y 4-y 2- (y1-y3) × y3r, wherein r is the increment of unit pixel coordinates, comparing the difference value between the two coordinates (x3, y3) and (x4, y4), if the difference value is smaller than a set threshold value, determining that the character area recognition result corresponding to the two coordinates is correct, and extracting and editing the recognized numbers and characters to form the brief description of the video.
3. The video integrated management platform system according to claim 1 or 2, wherein the data processing module includes a prediction module, and is configured to perform data processing on the acquired video data, and then store the video after data processing in a hard disk, specifically including: dividing a video image frame into a plurality of data blocks, predicting the pixel position pn of one data block at a time, wherein pn represents the predicted position of a pixel in an nth frame, and pn-1 is the position of a final pixel in the n-1 frame; an is a state transition matrix, on is An external control vector, Bn is An external control matrix, cn is a random variable, the predicted pixel position of the data block is compared with a pre-stored reference data block, whether the noise meets the condition is judged, if not, correction is carried out, if yes, the data block which is already predicted in the video image frame is marked, and all the data blocks are traversed.
4. The video integrated management platform system according to claim 3, wherein the prediction module comprises a comparison module, configured to compare the predicted pixel position of the data block with a pre-stored reference data block specifically: the position feature value of the extracted prediction data block is FA ═ (i, k), and the feature value of the extracted reference data block is FB ═ (j, t). If i < j, the prediction data block is smaller than the reference data block; if i > j, the prediction data block is larger than the reference data block; if i ═ j, then continue comparing k and t: if k < t, the prediction data block is smaller than the reference data block; if k > t, the prediction data block is larger than the reference data block; if (k ═ t and k ═ i +1) or (k ═ t and i-k ═ 0), the prediction data block is equal to the reference data block; otherwise, starting from the i-k-1 th bit of the prediction data block and the j-t-1 th bit of the reference data block, re-extracting the characteristic value FA (i, k) of the prediction data block and the characteristic value FB (j, t) of the reference data block in the direction of the low bit, and then repeating the steps.
5. the video integrated management platform system according to claim 4, wherein: when data acquisition is carried out on the area of the required video, a plurality of camera heads are adopted to carry out video monitoring acquisition.
6. The video integrated management platform system according to claim 5, wherein: and storing the video subjected to data processing into a hard disk, wherein the hard disk can be a temporarily stored mobile hard disk.
7. the video integrated management platform system according to claim 2, wherein: retrieving and inquiring video data stored in the cloud platform, downloading the retrieved video data and transmitting the retrieved video data to the terminal equipment of the user, and if the user needs to call a video record within a certain period of time, retrieving the required video through any terminal connected to the network, and downloading the video to the terminal equipment for watching.
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| CN201910870976.7A CN110545383A (en) | 2019-09-16 | 2019-09-16 | Video integrated management platform system |
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