CN112101234A - Detection code matching processing method and image code joint detection system - Google Patents
Detection code matching processing method and image code joint detection system Download PDFInfo
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The invention provides a detection code matching processing method and a graph code joint detection system, which comprise the following steps: step A1, extracting a plurality of second characteristic values associated with the first characteristic values from the archive; step A2, according to a preset time period, performing deduplication processing according to the collision situation of each second characteristic value at each monitoring station to obtain the number of collisions of each second characteristic value after deduplication and recording as the number of real collisions; step A3, respectively processing according to the real collision times to obtain the matching rate of each second characteristic value to the first characteristic value; and step A4, taking the matching rate of all the second characteristic values as the final matching result of the first characteristic values and storing the final matching result in an archive. The invention further matches the ISMI list in the formed archive base which takes the human face as the index, obtains the matching rate of each IMSI through the core matching algorithm, marks the IMSI with high matching rate, and can judge whether the data is effective according to the matching rate when the public security uses the data, thereby reasonably using the data and playing a useful role in detecting activities.
Description
Technical Field
The invention relates to the technical field of security and protection, in particular to a detection code matching processing method and a graph code joint detection system.
Background
With the rapid development of economy in China and the increasing complexity of safety and anti-terrorism situations at home and abroad, in some key control areas, for example: the security problems of the positions of the frontier inspection port, the tourist attractions and the like are more and more important, and aiming at the development trend of intelligentization, concealment and complication of crimes, the increasingly prominent security requirements are difficult to deal with only by the traditional security mode in the key sensitive areas, so that a new generation of security facilities is produced.
The new generation of security facilities mainly comprises: the device comprises face recognition, WIFI acquisition, wireless data acquisition (mobile phone electronic fence), license plate recognition, video monitoring and the like, social information is acquired in batches, the facility comprises a front-end device and background software, the front-end device can be deployed in public places, tourist attractions, specific areas, important facilities and traffic intersections, and can be deployed in indoor sites such as hotels, internet cafes, KTVs, bathing centers and the like and in mobile spaces such as buses and bus compartments. The background software is installed in the master control center, and is used for intelligently searching, comparing, controlling and tracking by combining related data such as an identity card, a license plate and the like through data analysis and data mining technologies according to information collected by the front end, providing timely, accurate and reliable action basis for police officers to monitor, track and arrest, and providing data and technical support for public security organs to develop social security management and control, anti-terrorism maintenance, investigation and solution solving and information analysis.
Application number CN201910804528.7 discloses a method for establishing an archive, which performs collision analysis on a face image, IMSI data (international mobile subscriber identity data) and MAC data (physical address data) according to a core algorithm to filter out a correct archive, thereby providing more accurate data support for users and providing powerful platform support for public security, security and the like. However, in this method, one face image itself will be matched to multiple IMSIs or MACs, although the IMSI of the person of the face image will be stored in the IMSI list of this archive, but multiple IMSIs are not all the IMSIs of the person of the face image, and the number of collisions of the IMSI will be displayed in the IMSI list, which is related to the capturing frequency, and the number of collisions is not necessarily the greater, the higher the matching rate is, for example, if the number of collisions per unit time is too large, if there is no duplication, the accuracy of the used data will be affected by the manner of local collection.
Disclosure of Invention
The invention provides a detection code matching processing method and a graph code joint detection system, and aims to solve the problem that objective matching relation of face images cannot be intuitively reflected in the prior art, so that public security workers can more effectively use data to conduct detection activities.
A detection code matching processing method is suitable for a graphic code joint detection system,
the image code joint detection system comprises an archive, wherein a first characteristic value which is acquired from each monitoring station and used for representing a face image and a second characteristic value which is used for representing a unique identification code of the mobile equipment are stored in the archive in advance;
in the code matching processing method, the following steps are respectively executed for each first characteristic value in the archive:
step A1, extracting a plurality of second characteristic values associated with the first characteristic values from the archive;
step A2, according to a preset time period, performing deduplication processing according to the collision situation of each second characteristic value at each monitoring station to obtain the number of collisions of each second characteristic value after deduplication and recording as the number of real collisions;
step A3, respectively processing according to the real collision times to obtain the matching rate of each second characteristic value to the first characteristic value;
and step A4, taking the matching rate of all the second characteristic values as the final matching result of the first characteristic values and storing the final matching result in an archive.
Further, after performing step a2, the following steps are first performed:
step B1, matching the second characteristic value with a pre-stored resident characteristic value set, and judging whether the second characteristic value is a resident characteristic value:
if yes, go to step B2;
if not, go to step B3;
step B2, filtering the second characteristic value from the archive, and then entering step B4;
step B3, retaining the second feature value, and then entering step B4;
step B4, after each second feature value associated with the first feature value is determined, step A3 is entered.
Further, the second characteristic value is an IMSI number of the mobile device.
Further, the second characteristic value is the MAC address of the mobile device.
Further, in step a3, the specific calculation formula of the matching rate of each second eigenvalue to the first eigenvalue is obtained by processing according to the number of real collisions respectively as follows:
wherein the content of the first and second substances,
Cirepresenting the number of times of collision of the currently calculated second characteristic value acquired on the ith acquisition station;
n represents the number of acquisition sites acquiring the currently calculated second characteristic value;
k represents the number of the collecting stations for collecting the jth second characteristic value;
m represents the number of the extracted second eigenvalues;
Ci,jshowing that the jth second characteristic value is at the ith acquisition site AiAnd acquiring the collision times of the jth second characteristic value.
Further, in step a3, the m second feature values are obtained as follows:
step A31, sorting the second eigenvalues in descending order according to the number of acquisition sites acquiring the second eigenvalues;
step a32, extracting m second feature values that are ranked in the front.
Further, in step a4, the second eigenvalues are sorted in descending order of the matching rate, and the second eigenvalues whose matching rate is greater than the preset number rate are labeled.
A graphic code joint detection system is applied to the detection code matching processing method, and comprises the following steps:
the mobile device comprises an archive, a plurality of monitoring sites and a plurality of mobile devices, wherein a first characteristic value used for representing a face image and a second characteristic value used for representing a unique identification code of the mobile device, which are acquired from each monitoring site, are stored in the archive in advance;
the characteristic extraction module is connected with the archive and used for extracting a plurality of second characteristic values related to the first characteristic values from the archive;
the duplicate removal processing module is connected with the characteristic extraction module and is used for carrying out duplicate removal processing according to the collision condition of each second characteristic value at each monitoring station according to a preset time period to obtain the collision frequency of each second characteristic value after duplicate removal and recording the collision frequency as the real collision frequency;
the matching rate obtaining module is connected with the duplicate removal processing module and is used for respectively processing according to the real collision times to obtain the matching rate of each second characteristic value to the first characteristic value;
and the storage module is connected with the matching rate acquisition module and used for taking the matching rates of all the second characteristic values as the final matching result of the first characteristic value and storing the final matching result in the archive.
The beneficial technical effects of the invention are as follows: the invention further matches the ISMI list in the formed archive base which takes the human face as the index, obtains the matching rate of each IMSI through the core matching algorithm, marks the IMSI with high matching rate, and can judge whether the data is effective according to the matching rate when the public security uses the data, thereby reasonably using the data and playing a useful role in detecting activities.
Drawings
FIG. 1 is a flowchart illustrating the steps of a detection code matching method according to the present invention;
FIG. 2 is a flowchart illustrating the steps of a detection code matching method according to the present invention;
FIG. 3 is a flowchart illustrating the steps of a detection code matching method according to the present invention;
fig. 4 is a diagram illustrating a calculation result of a detection code matching processing method according to the present invention.
FIG. 5 is a block diagram of a code association detection system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
The present invention is based on a method for creating an archive disclosed in application No. CN201910804528.7, the entire contents of which are incorporated herein by reference.
Referring to fig. 1-3, the present invention provides a method for detecting code matching,
the method is suitable for a graphic code joint detection system, the graphic code joint detection system comprises an archive library, first characteristic values which are acquired from all monitoring sites and used for representing face images and second characteristic values which are used for representing unique identification codes of mobile equipment are stored in the archive library in advance, the first characteristic values acquired by all the monitoring sites are respectively associated with a plurality of corresponding second characteristic values, and each second characteristic value has the number of times of collision acquired at all the monitoring sites;
in the code matching processing method, the following steps are respectively executed for each first characteristic value in the archive:
step A1, extracting a plurality of second characteristic values associated with the first characteristic values from the archive;
step A2, according to a preset time period, performing deduplication processing according to the collision situation of each second characteristic value at each monitoring station to obtain the number of collisions of each second characteristic value after deduplication and recording as the number of real collisions;
step A3, respectively processing according to the real collision times to obtain the matching rate of each second characteristic value to the first characteristic value;
step A4, using the matching rate of all the second eigenvalues as the final matching result of the first eigenvalue and storing the final matching result in the archive
Specifically, in step a3, the specific calculation formula of the matching rate of each second eigenvalue to the first eigenvalue is obtained by processing according to the number of real collisions, as follows:
wherein the content of the first and second substances,
Aian ith acquisition site representing a currently calculated second feature value;
Cishown at the ith acquisition site AiAcquiring the number of collisions of the currently calculated second characteristic value;
f(Ai) Shown at the ith acquisition site AiAcquiring a weighting function of the collision times of the currently calculated second characteristic value;
n represents the number of acquisition sites acquiring the currently calculated second characteristic value;
k represents the number of the collecting stations for collecting the jth second characteristic value;
m represents the number of the extracted second eigenvalues;
Ci,jshowing that the jth second characteristic value is at the ith acquisition site AiNumber of collisions of the j-th second feature valueCounting;
f(Ai,j) Showing that the jth second characteristic value is at the ith acquisition site AiAcquiring a weighting function of the collision times of the jth second characteristic value;
and A4, sorting the second characteristic values according to the descending order of the matching rate, and marking the second characteristic values with the matching rate larger than the preset number rate.
Further, after performing step a2, the following steps are first performed:
step B1, matching the second characteristic value with a pre-stored resident characteristic value set, and judging whether the second characteristic value is a resident characteristic value:
if yes, go to step B2;
if not, go to step B3;
step B2, filtering the second characteristic value from the archive, and then entering step B4;
step B3, retaining the second feature value, and then entering step B4;
step B4, after each second feature value associated with the first feature value is determined, step A3 is entered.
Further, the first feature value is a face image.
Further, the second characteristic value is an IMSI number of the mobile device, and the second characteristic value is an international mobile subscriber identity of the mobile phone.
Further, the second characteristic value is the MAC address of the mobile device, and the second characteristic value is the physical address of the mobile phone.
Further, in step a3, the m second feature values are obtained as follows:
step A31, sorting the second eigenvalues in descending order according to the number of acquisition sites acquiring the second eigenvalues;
step a32, extracting m second feature values that are ranked in the front.
Further, m is 10.
Further, f (A)i) The value of (a) is the number of the acquisition sites acquiring the second characteristic values, and the matching of each second characteristic value to the first characteristic value is calculatedThe formula for the rate is as follows:
further, the unit time period was 10 minutes.
Further, the unit time period is 1 hour.
The present invention is based on a method for creating an archive disclosed in application No. CN201910804528.7, the entire contents of which are incorporated herein by reference. On the basis, the invention further matches the ISMI list in the formed archive base which takes the human face as the index, obtains the matching rate of each IMSI through the core matching algorithm, marks the IMSI with high matching rate, and can judge whether the data is effective according to the matching rate when the public security uses the data, thereby reasonably using the data and playing a useful role in investigating the activity.
In the invention, the collision times of each second characteristic value collected in the unit time period are subjected to deduplication processing, so that the collision capture effect of each collection station is consistent, the accuracy of the whole algorithm cannot be influenced by the capture strategy of a local area, and the unit time period can be adjusted according to the conditions of the field environment and the like.
In the invention, for some collection sites, some devices are collected frequently, such as mobile phones of site workers, and before the matching rate is calculated, second characteristic values of the devices are deleted and filtered, namely the devices are filtered, so that real targets are obtained more accurately.
In the present invention, if an IMSI can be collided at multiple sites, its matching rate is high, and it is likely to be the target to be searched. Therefore, the second characteristic values are sorted according to the descending order of the number of the acquisition sites for acquiring the second characteristic values, and m second characteristic values arranged in the front are extracted to calculate the matching rate, so that the effectiveness of the data is improved, and the method is very favorable for finding a real target. On the basis, f (A) is directly addedi) The number of the acquisition stations is used for replacing the number of the acquisition stations, so thatTo a simplified matching ratio formula:
for each second characteristic value j, the corresponding number k of the acquisition stations is different.
Referring to fig. 4, after sorting according to the descending order of the matching rates, the matching rate of the IMSI information in the first row of 460020825573749 is the highest, the number of collisions (i.e., the number of accompaniments) of the IMSI information in the second row of 460110123216455 is the highest, but the validity of the IMSI information in the first row of 460020825573749 is higher than that of the IMSI information in the second row of 460110123216455.
In the present invention, the matching rate of the mac data (physical address data) for the face image can be calculated using the same calculation method.
Further, in step a4, the second eigenvalues are sorted in descending order of the matching rate, and the second eigenvalues whose matching rate is greater than the preset number rate are labeled.
Referring to fig. 5, the present invention further provides a graph code joint detection system, which applies the detection code matching processing method described above, including:
the mobile terminal comprises an archive (1) and a plurality of monitoring stations, wherein a first characteristic value used for representing a face image and a second characteristic value used for representing a unique identification code of the mobile device, which are acquired from each monitoring station, are stored in the archive in advance;
the characteristic extraction module (2) is connected with the archive (1) and is used for extracting a plurality of second characteristic values associated with the first characteristic values from the archive (1);
the de-duplication processing module (3) is connected with the characteristic extraction module (2) and is used for performing de-duplication processing on the collision condition of each monitoring station according to each second characteristic value according to a preset time period to obtain the de-duplicated collision times of each second characteristic value and recording the de-duplicated collision times as the real collision times;
the matching rate obtaining module (4) is connected with the duplicate removal processing module (3) and is used for respectively processing according to the real collision times to obtain the matching rate of each second characteristic value to the first characteristic value;
and the storage module (5) is connected with the matching rate acquisition module (4) and is used for taking the matching rates of all the second characteristic values as the final matching result of the first characteristic values and storing the final matching result in the archive.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (8)
1. A detection code matching processing method is suitable for a graphic code joint detection system, and is characterized in that,
the image code joint detection system comprises an archive, wherein a first characteristic value which is acquired from each monitoring station and used for representing a face image and a second characteristic value which is used for representing a unique identification code of mobile equipment are stored in the archive in advance, in the archive, the first characteristic value acquired by each monitoring station is respectively associated with a plurality of corresponding second characteristic values, and each second characteristic value respectively has the number of times of collision acquired at each monitoring station;
in the code detection matching processing method, for each first feature value in the archive, the following steps are respectively performed:
a step a1 of extracting a plurality of second feature values associated with the first feature value from the archive;
step A2, according to a preset time period, performing deduplication processing according to the collision situation of each second eigenvalue at each monitored station, obtaining the collision frequency of each second eigenvalue after deduplication, and recording the collision frequency as a real collision frequency;
step A3, respectively processing according to the real collision times to obtain the matching rate of each second eigenvalue to the first eigenvalue;
and step A4, taking the matching rate of all the second characteristic values as the final matching result of the first characteristic values and storing the final matching result in the archive.
2. The method of claim 1, wherein after performing step a2, the following steps are first performed:
step B1, matching the second eigenvalue with a pre-stored resident eigenvalue set, and determining whether the second eigenvalue is a resident eigenvalue:
if yes, go to step B2;
if not, go to step B3;
step B2, filtering the second feature value from the archive, and then entering step B4;
step B3, retaining the second feature value, and then proceeding to step B4;
step B4, after each second feature value associated with the first feature value is determined, the process proceeds to step A3.
3. The method of claim 1, wherein the second characteristic value is an IMSI number of the mobile device.
4. The method of claim 1, wherein the second characteristic value is a MAC address of the mobile device.
5. The method as claimed in claim 1, wherein in step a3, the specific calculation formula of the matching rate of each second eigenvalue to the first eigenvalue is obtained by processing according to the number of true collisions respectively as follows:
Cirepresenting the number of collisions of the second feature value which is currently calculated on the ith acquisition station;
n represents the number of acquisition sites acquiring the second feature value currently calculated;
k represents the number of acquisition sites acquiring the jth second characteristic value;
m represents the number of the extracted second feature values;
Ci,jrepresents that the jth second characteristic value is at the ith acquisition site AiAnd acquiring the collision times of the jth second characteristic value.
6. The method of claim 5, wherein m second feature values are obtained in step A3 as follows:
step A31, sorting the second eigenvalues in descending order of the number of acquisition sites acquiring the second eigenvalues;
step a32, extracting m first-ranked second feature values.
7. The method as claimed in claim 6, wherein in step a4, the second feature values are sorted in descending order of the matching rate, and the second feature values with the matching rate greater than a predetermined number rate are marked.
8. A combined detection system for image codes, which is applied to a detection code matching processing method according to any one of claims 1 to 7, and comprises:
the mobile terminal comprises an archive, a plurality of monitoring sites and a plurality of mobile terminals, wherein a first characteristic value used for representing a face image and a second characteristic value used for representing a unique identification code of the mobile terminal, which are acquired from each monitoring site, are stored in the archive in advance;
the characteristic extraction module is connected with the archive and used for extracting a plurality of second characteristic values related to the first characteristic values from the archive;
the duplication elimination processing module is connected with the feature extraction module and used for carrying out duplication elimination processing according to the collision condition of each second feature value at each monitoring station according to a preset time period to obtain the duplication eliminated collision times of each second feature value and recording the collision times as real collision times;
the matching rate obtaining module is connected with the duplicate removal processing module and is used for respectively processing according to the real collision times to obtain the matching rate of each second characteristic value to the first characteristic value;
and the storage module is connected with the matching rate acquisition module and used for taking the matching rate of all the second characteristic values as a final matching result of the first characteristic values and storing the final matching result in the archive.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112579588A (en) * | 2020-12-30 | 2021-03-30 | 南京宏之图信息技术有限公司 | Method for searching and accurately matching multiple groups of time sequence data based on dichotomy |
| CN112925899A (en) * | 2021-02-09 | 2021-06-08 | 重庆中科云从科技有限公司 | Ranking model establishing method, case clue recommending device and medium |
| CN113255618A (en) * | 2021-07-07 | 2021-08-13 | 武汉中科通达高新技术股份有限公司 | Data collision method and device |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105790955A (en) * | 2016-04-06 | 2016-07-20 | 深圳市博康智能信息技术有限公司 | Method and system for associating MAC addresses with face information |
| CN106453691A (en) * | 2016-11-29 | 2017-02-22 | 山东合天智汇信息技术有限公司 | Method and system for binding MAC real identity |
| CN106874347A (en) * | 2016-12-26 | 2017-06-20 | 深圳市深网视界科技有限公司 | A kind of method and system for matching characteristics of human body and MAC Address |
| CN109086829A (en) * | 2018-08-14 | 2018-12-25 | 东方网力科技股份有限公司 | A kind of method and device that social population administers |
| CN109614450A (en) * | 2018-12-05 | 2019-04-12 | 武汉烽火众智数字技术有限责任公司 | The method and system of personnel's whereabouts analysis based on multidimensional data |
| CN109634946A (en) * | 2018-12-06 | 2019-04-16 | 南京森根科技发展有限公司 | A kind of track intelligent Matching association analysis algorithm model excavated based on big data |
| CN109635760A (en) * | 2018-12-18 | 2019-04-16 | 深圳市捷顺科技实业股份有限公司 | A kind of face identification method and relevant device |
| CN109947758A (en) * | 2019-04-03 | 2019-06-28 | 深圳市甲易科技有限公司 | A kind of route crash analysis method in Behavior-based control track library |
| CN109977108A (en) * | 2019-04-03 | 2019-07-05 | 深圳市甲易科技有限公司 | A kind of a variety of track collision analysis methods in Behavior-based control track library |
| CN110502521A (en) * | 2019-08-28 | 2019-11-26 | 上海寰创通信科技股份有限公司 | A kind of method for building up of file store |
| CN110751042A (en) * | 2019-09-19 | 2020-02-04 | 任子行网络技术股份有限公司 | Time partition-based portrait and IMSI information association method and system |
| CN110781336A (en) * | 2019-09-30 | 2020-02-11 | 任子行网络技术股份有限公司 | Method and system for fusing portrait data and mobile phone feature data based on global filing |
| CN110874369A (en) * | 2019-10-25 | 2020-03-10 | 广州纳斯威尔信息技术有限公司 | Multidimensional data fusion investigation system and method thereof |
| CN111615062A (en) * | 2020-05-12 | 2020-09-01 | 博康云信科技有限公司 | Target person positioning method and system based on collision algorithm |
-
2020
- 2020-09-16 CN CN202010976934.4A patent/CN112101234B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105790955A (en) * | 2016-04-06 | 2016-07-20 | 深圳市博康智能信息技术有限公司 | Method and system for associating MAC addresses with face information |
| CN106453691A (en) * | 2016-11-29 | 2017-02-22 | 山东合天智汇信息技术有限公司 | Method and system for binding MAC real identity |
| CN106874347A (en) * | 2016-12-26 | 2017-06-20 | 深圳市深网视界科技有限公司 | A kind of method and system for matching characteristics of human body and MAC Address |
| CN109086829A (en) * | 2018-08-14 | 2018-12-25 | 东方网力科技股份有限公司 | A kind of method and device that social population administers |
| CN109614450A (en) * | 2018-12-05 | 2019-04-12 | 武汉烽火众智数字技术有限责任公司 | The method and system of personnel's whereabouts analysis based on multidimensional data |
| CN109634946A (en) * | 2018-12-06 | 2019-04-16 | 南京森根科技发展有限公司 | A kind of track intelligent Matching association analysis algorithm model excavated based on big data |
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