CN112911581A - Mobile phone number query method and system based on cross-correlation calculation - Google Patents
Mobile phone number query method and system based on cross-correlation calculation Download PDFInfo
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04M1/274—Devices whereby a plurality of signals may be stored simultaneously with provision for storing more than one subscriber number at a time, e.g. using toothed disc
- H04M1/2745—Devices whereby a plurality of signals may be stored simultaneously with provision for storing more than one subscriber number at a time, e.g. using toothed disc using static electronic memories, e.g. chips
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Abstract
The invention relates to a mobile phone number query method based on a cross-correlation algorithm, which solves the correlation comparison of various data objects by providing a comparison algorithm based on the cross-correlation, further performs the visualization of a result set with extremely high similarity through the cross-correlation comparison of IMSI and photos in a period of time, and reduces the complexity calculation of time and space through algorithm optimization. When a user inputs a target photo, the time parameter-based photo set feature function is established for an acquired information source in a database, and the similarity between image information is calculated; meanwhile, according to the number of different IMSIs in the corresponding time period in the photo set, forming characteristic functions with correlation; and performing cross-correlation function calculation on the two and performing normalization operation for removing interference to obtain a similarity value, and visualizing the IMSI information result set with the most correlation and the original target photo to a user interface.
Description
Technical Field
The invention relates to a mobile phone number query method and a mobile phone number query system based on cross-correlation calculation, in particular to the technical field of similarity comparison based on cross-correlation comparison between IMSI and collected images.
Background
With the increasing sophistication of data mining and analysis technologies, emerging data collection and processing technologies are also expanding and perfecting in an exponentially growing fashion. The similarity between data becomes an important reference basis for the relevance analysis of the data, and at present, the analysis of the relevance value of the data becomes the point of the researcher analyzing the disordered data and redefining the data value.
The existing similarity analysis is only the comparison between single numerical objects, generally is the comparison between single text analysis or single pixel points between images, is only suitable for specific comparison objects without relevance, and adopts a mode of reading all numerical values by circular traversal, thereby increasing the operation complexity during calculation.
Disclosure of Invention
The purpose of the invention is as follows: the method for inquiring the mobile phone number based on the cross-correlation calculation is provided to solve the problems in the prior art. The further purpose is to complete the mobile phone number query of the target person by combining the correlation of the collected photo set and the IMSI information.
The technical scheme is as follows: a mobile phone number query method based on cross-correlation calculation comprises the following steps:
step 1, acquiring image information and IMSI information of a passing person through information acquisition equipment, and acquiring a data source;
in a further embodiment, the image data is acquired by shooting the face and storing face image information and shooting time when the face enters the shooting range of the face acquisition device, and the image information acquired by the information device ensures that shooting time points which are far away from each other are visible on the division of a time axis, namely, the time range of the number of the target object is not overlapped;
the IMSI data source is the number of times that the IMSI collected by the information acquisition equipment sends a registration request to the equipment within a certain time period when a certain person arrives at a shooting place.
Step 2, inputting a target query photo, comparing the target query photo with data in a database, and processing the queried data to reduce the computational complexity;
the IMSI screening with similarity is firstly carried out on the input target photos, a small range of time periods before and after a time point is taken, and only the number appearing in the time period is considered during calculation, so that the time complexity caused by the unrelated data during the cross-correlation calculation is reduced, namely the IMSI information and the number appearing in each 30 seconds before and after the searched photo shooting are adopted in the method.
Step 3, performing relevance analysis on multiple groups of data by using a cross-correlation function;
the similarity is determined by calculating a discrete function presented by a group of photos on a time axis and a cross-correlation function of each IMSI, and the cross-correlation function formula of the two objects is as follows:
wherein Pic (t) represents a discrete function related to a photo set, τ in Imsi (τ + t) represents a time difference, the overall functional expression is a discrete function of Imsi in a shooting time period, and the judgment is based on the more similarity by directly checking the total number of valid points of all cross-correlation functions.
The basis of judging more similarity is that the total number of effective points of all cross-correlation functions is directly checked, but in order to reduce the interference of resident and frequently-passing objects, the solution of cross-correlation function normalization is adopted to compress the energy of the whole cross-correlation function to 1, namely, the total number of IMSIs is divided by one, and the total number of photos is divided by one, and the calculation formula is as follows:
after the processing of the above steps, when it is established that the time difference between two images is greater than the interval size, that is, only one number is paired with one photo, for the same photo set, only which IMSI is more similar to the photo set for the energy and size characterization meeting the conditions in the cross-correlation function of different IMSIs, and the calculated result is that any number-adding time of some IMSI can only correspond to the shooting time of some photo in the photo set, that is, under the model, the calculated maximum value of energy is one-tenth of the total number of photos, and based on this multiplication by the total number of photos, the similarity between the target and some IMSI when any target has a photo set of any size can be made, the calculation formula is:
after the complexity reduction is performed preliminarily, the remaining comparison data volume is reduced to a greater extent, and in order to reduce misleading phenomena caused by fuzzy objects or fuzzy photos, the photo function does not adopt the number of the photo at each moment, but multiplies the credibility of the photo function on the original basis, and the calculation formula is as follows:
in combination with all the calculated values, the overall implemented cross-correlation calculation formula in the scheme under the combination of normalization and confidence is:
step 4, performing visual presentation on the processed result set;
and performing descending order arrangement on the calculated similarity result sets, performing layout realization on a visual interface by utilizing a front-end development design language, and displaying the result set which is arranged in front and has the most similarity to the visual interface visible to a user by selecting the information result set through a data interaction technology.
Has the advantages that: the invention relates to a mobile phone number query method based on cross-correlation calculation, which solves the correlation comparison of various data objects by providing a comparison algorithm based on cross-correlation, further performs the visualization of a result set with extremely high similarity through the cross-correlation comparison of IMSI and photos in a period of time, and reduces the complexity calculation of time and space through algorithm optimization. When a user inputs a target photo, a photo set with high similarity to a target value can be obtained, meanwhile, the corresponding IMSI is obtained according to the time range of photo shooting, the same IMSI is summed, the calculated numerical value is used as the similarity, and the most front IMSI result set and the similarity are visualized to a user interface after the similarity numerical values are arranged in a descending order.
Drawings
Fig. 1 is a block diagram of a mobile phone number query method based on cross-correlation calculation according to the present invention.
Fig. 2 is a flowchart of an implementation of the method for querying a mobile phone number based on cross-correlation calculation according to the present invention.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention. It will be apparent, however, to one skilled in the art, that the present invention may be practiced without one or more of these specific details. In other instances, well-known features have not been described in order to avoid obscuring the invention.
As shown in fig. 1, a flow chart of a mobile phone number query method based on cross-correlation calculation is specifically implemented as follows:
firstly, a user inputs target person picture information to be retrieved by using a terminal on an interface, the similarity of a picture of a target person is compared with a person picture collected in a face information database through program setting, a series of face pictures with extremely high similarity are selected as a result set to be recommended, and a discrete function with time and similarity probability as parameters is formed. Secondly, under the operation of the program, the shooting time point corresponding to each photo in the photo set is read, and a period of time before and after the shooting time point of the photo is set as a time period according to which the IMSI signal is inquired. And thirdly, searching for different IMSIs in corresponding time periods from the selected time periods to a database for storing the IMSI, and forming a discrete function of each IMSI by taking time and the number of times as parameters according to the division of the time periods. From time to time, cross-correlation calculations of two discrete functions are performed with the aid of program aided calculations. And finally, sorting the calculated result values, selecting the numerical values of the first three, and displaying the corresponding IMSI including the mobile phone number information and the input target photo on a user visual terminal interface, wherein the specific implementation flow chart is shown in FIG. 2.
When the face image information and the shooting time are collected and stored in a warehouse, the defined picture shooting time point is the time point when the person just starts to enter the camera equipment, and in order to prevent the situation that a plurality of pieces of image information are collected in a very short time range by the same person and useless IMSI appears in relevant time periods in the later period, the time interval for storing the picture information of the same person in the face database is large, namely when the pictures are stored in the warehouse, if two pictures are judged to be very similar, the second collected picture is discarded, and the two obtained pictures are ensured to be far away in the time axis.
The number-up times defined in the storage database of the IMSI is the registration times reported by the terminal equipment, namely when a person carries a mobile phone and passes through the information acquisition terminal equipment, the IMSI sends registration to the acquisition equipment once in two to three seconds, and the equipment records the IMSI information and the registration times sent by the IMSI at a time point.
The discrete functions generated by the photo set and the discrete functions generated by different IMSIs are subjected to cross-correlation calculation, the cross-correlation value is the similarity between the photo set and the IMSIs, and the calculation time complexity and the calculation space complexity are greatly increased when the exhaustive method is used for circularly reading all IMSI information to perform cross-correlation calculation comparison, so that the operation efficiency is improved for reducing consumption. The usage of the cross-correlation calculation in the present scheme is that a cross-correlation function value expressed as a certain IMSI and a target photo set is in a time range of τ, the number of photos of a target object at each time point is multiplied by the number of IMSIs at a time point delayed by τ seconds at the time point, and then the sum is added, and the basis for judging the existence of correlation between the two objects is that a point with a value, energy and weight exists in the time range of τ, and the calculation formula is as follows:
wherein Pic (t) represents a discrete function related to a photo set, τ in Imsi (τ + t) represents a time difference, the overall functional expression is a discrete function of Imsi in a shooting period, the judgment is based on the basis of more similarity by directly checking the total number of valid points of all cross-correlation functions, but in order to reduce the interference of resident and frequently-passing objects, a solution of cross-correlation function normalization is adopted, in the scheme, in order to remove interference terms to better judge which one of the photo sets is more correlated with a target person, normalization processing is adopted to compress the energy of the whole cross-correlation function to 1, that is, the corresponding operation is to divide the total number of Imsi by the total number of one photo and divide by the total number of one photo, and the calculation formula is as follows:
the division by the total number of photos in the above calculation formula is only for the purpose of removing interference by normalization, and in actual calculation, the similarity is lower as the number of photos in the photo set is larger, because the time period covered by each photo is independent and non-repetitive, each IMSI number-adding time point that can be corresponded is not corresponded to x-1 photos, so that x-1 times of non-correspondence is generated, wherein the variable x represents the number of photos. The energy and size of the cross correlation functions of different IMSIs that are eligible can only indicate which are more similar for the same photo set. After the processing of the above steps, it is established that when the time difference between two images is greater than the interval size, that is, on the basis that one number is only paired with one photo, for the same photo set, only the energy and size characteristics meeting the conditions in the cross-correlation functions of different IMSIs are more similar, so that the calculated result is that all IMSI numbering times of some IMSI can correspond to the shooting time of some photo in some photo set, and the energy and maximum meeting the conditions in the finally obtained cross-correlation function can only be (1/total number of photos), on the basis that one number is paired with one photo, we multiply the total number of photos, so that any target can have a photo set of any size, and when the IMSI completely corresponds to this target, the similarity is 1, that is, the calculation formula is converted into the following calculation formula:
the similarity of approximately 85% and 90% exists between each photo and the given target photo, when the similarity of a certain photo and the target photo is originally low, the reliability of the IMSI number-adding time corresponding to the certain photo is reduced, in order to reduce the similarity and reduce the generation of misleading phenomena, the photo function adopts the reliability of the IMSI number-adding time on the basis of the original reliability instead of the number of each moment, and the similarity of the target and the number is not more than hundred percent. The credibility of each photo in the photo set is applied during calculation, that is, the photo function does not directly use the number of each photo at each moment, but multiplies the credibility by the number of each photo, and the calculation formula is as follows:
wherein P (t) is expressed as a discrete function of the credibility of the corresponding photos in the photo set, and finally, the cross-correlation value between the two is calculated in a total way, and the calculation formula is as follows:
and sequencing the finally calculated numerical values, selecting the three IMSIs with the highest ranking, performing layout design on a user visible interface by using a visual programming language, selecting and displaying the result set with the highest similarity which is arranged in the front by using a data interaction technology to the user visible visual interface, and displaying the target retrieval picture, the IMSI information and the corresponding mobile phone number by using a simple visual interface.
Based on the method, a mobile phone number corresponding query system based on a cross-correlation algorithm can be constructed, and the method comprises the following steps:
the first module is used for collecting a data source and establishing a database to be compared; the data source of the IMSI database to be compared is the number of times and the time period of reporting and registering the IMSI and the equipment when the mobile phone carried by the object passes through the information acquisition equipment terminal.
A second module for constructing an easily operable visual interface; the module carries out layout design of a visual interface through a corresponding programming language, the constructed interface guides a user to input information of a target photo, and a finally calculated recommendation result is displayed on a screen.
A third module for cross-correlation function correlation application; the module respectively constructs a discrete photo function set and an IMSI discrete function from the preliminarily found photo set and IMSI set, realizes the following calculation modes by using operations such as normalization, reliability improvement and the like, and calculates the value of similarity by using the following formula:
and sorting the calculated values according to the sizes, selecting the three IMSIs with the top ranking, presenting the information result set to a visual interface visible to a user through a data interaction technology, and presenting the target retrieval picture, the IMSI information and the corresponding mobile phone number by using a simple visual interface.
Under the technical scheme, the specific using process of the invention is as follows: for example, when a police pursuits a target and inquires the situation that the police possibly has a mobile phone number, by using the method and the system disclosed by the invention, in a visual operation interface, through inputting an image file of a target photo at a user terminal, and by using a method for calculating multiple groups of IMSIs corresponding to multiple photos and weights thereof and summing the same IMSIs to obtain similar values, under the condition of finishing result sorting, a high-similarity result set obtained through reasonable calculation can be checked in the visual interface, namely, the photo of the target person to be searched, the 3 IMSIs with the highest similarity and the corresponding mobile phone numbers thereof, so that the aim of inquiring the mobile phone number is fulfilled.
As noted above, while the present invention has been shown and described with reference to certain preferred embodiments, it is not to be construed as limited thereto. Various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. A mobile phone number query method based on cross-correlation calculation is characterized by comprising the following steps:
step 1, acquiring passerby face image information and IMSI information of a portable communication device through information acquisition equipment, and storing the information as a comparison data source;
step 2, a user inputs a target query photo, compares the target query photo with data in a database, processes the queried data to establish a function model, deletes the data and reduces the complexity of post-computation;
step 3, performing relevance analysis on multiple groups of data by using a cross-correlation function;
and 4, visualizing the processed result set to a user interface.
2. The method for querying mobile phone numbers based on cross-correlation calculation as claimed in claim 1, wherein the step 1 further comprises:
the acquisition of image data is that when a human face enters a shooting range of the human face acquisition equipment, human face shooting and storage of human face image information and shooting time are carried out, and picture information acquired by the information equipment ensures that shooting time points which are far away from each other are visible on the division of a time axis, namely, no overlapping of time ranges exists in the time range of the number of a target object;
the IMSI data source is the number of times that the IMSI collected by the information acquisition equipment sends a registration request to the equipment within a certain time period when a certain person arrives at a shooting place.
3. The method for querying mobile phone numbers based on cross-correlation calculation as claimed in claim 1, wherein the step 2 further comprises:
and firstly carrying out IMSI screening with similarity on the input target photos, taking a small-range time period before and after a time point, and only considering the number appearing in the time period during calculation so as to reduce the time complexity caused by the unrelated data during the cross-correlation calculation.
4. The method for querying mobile phone numbers based on cross-correlation calculation as claimed in claim 1, wherein the step 3 further comprises:
the similarity is determined by calculating a discrete function presented by a group of photos on a time axis and a cross-correlation function of each IMSI, and a cross-correlation function formula of two objects is defined as follows:
wherein Pic (t) represents a discrete function related to a photo set, τ in Imsi (τ + t) represents time difference, the integral functional expression of Imsi (τ + t) is a discrete function of IMSI in a shooting time period, and the judgment is based on the more similarity by directly checking the total number of valid points of all cross-correlation functions;
the basis of judging more similarity is that the total number of effective points of all cross-correlation functions is directly checked, but in order to reduce the interference of resident and frequently-passing objects, the solution of cross-correlation function normalization is adopted to compress the energy of the whole cross-correlation function to 1, namely, the total number of IMSIs is divided by one, and the total number of photos is divided by one, and the calculation formula is as follows:
after the processing of the above steps, when it is established that the time difference between two images is greater than the interval size, that is, only one number is paired with one photo, for the same photo set, only which IMSI is more similar to the photo set for the energy and size characterization meeting the conditions in the cross-correlation function of different IMSIs, and the calculated result is that any number-adding time of some IMSI can only correspond to the shooting time of some photo in the photo set, that is, under the model, the calculated maximum value of energy is one-tenth of the total number of photos, and based on this multiplication by the total number of photos, the similarity between the target and some IMSI when any target has a photo set of any size can be made, the calculation formula is:
after the complexity reduction is performed preliminarily, the remaining comparison data volume is reduced to a greater extent, and in order to reduce misleading phenomena caused by fuzzy objects or fuzzy photos, the photo function does not adopt the number of each moment, but multiplies the reliability of the photo function by the original basis, and the calculation formula is as follows:
the overall combined cross-correlation calculation formula, combining all the calculated values, is:
5. the method for querying mobile phone numbers based on mutual correlation calculation as claimed in claim 1, wherein said step 4 is further:
and performing descending order arrangement on the calculated similarity result sets, performing layout realization on a visual interface by utilizing a front-end development design language, and displaying the result set which is arranged in front and has the most similarity to the visual interface visible to a user by selecting the information result set through a data interaction technology.
6. A mobile phone number query system based on cross-correlation calculation, for executing the mobile phone number query method based on cross-correlation calculation in claim 1, characterized by comprising the following modules:
the first module is used for collecting a data source and establishing a database to be compared; the data source of the IMSI database to be compared is the number of times and the time period of reporting and registering the IMSI and the equipment when an object carrying a mobile phone passes through the terminal of the information acquisition equipment;
a second module for constructing an easily operable visual interface; the module carries out layout design of a visual interface through a corresponding programming language, the constructed interface guides a user to input information of a target photo, and a finally calculated recommendation result is displayed on a screen;
a third module for cross-correlation function correlation application; the module respectively constructs a discrete photo function set and an IMSI discrete function from the preliminarily found photo set and IMSI set, realizes the following calculation modes by using operations such as normalization, reliability improvement and the like, and calculates the value of similarity by using the following formula:
and sorting the calculated values according to the sizes, selecting the three IMSIs with the top ranking, presenting the information result set to a visual interface visible to a user through a data interaction technology, and presenting the target retrieval picture, the IMSI information and the corresponding mobile phone number by using a simple visual interface.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016180272A1 (en) * | 2015-05-12 | 2016-11-17 | 杭州海康威视数字技术股份有限公司 | Image acquisition method and device, and video monitoring method and system |
| CN106940794A (en) * | 2017-03-23 | 2017-07-11 | 中国电子科技集团公司第三十八研究所 | A yard adjoint system is detectd in a kind of target collection |
| US20180121737A1 (en) * | 2016-09-26 | 2018-05-03 | Verint Systems Ltd. | System and method for associating an identifier of a mobile communication terminal with a person-of-interest, using video tracking |
| CN110727809A (en) * | 2019-09-27 | 2020-01-24 | 上海依图网络科技有限公司 | Face and mobile user identification code association query method and device and electronic equipment |
-
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016180272A1 (en) * | 2015-05-12 | 2016-11-17 | 杭州海康威视数字技术股份有限公司 | Image acquisition method and device, and video monitoring method and system |
| US20180121737A1 (en) * | 2016-09-26 | 2018-05-03 | Verint Systems Ltd. | System and method for associating an identifier of a mobile communication terminal with a person-of-interest, using video tracking |
| CN106940794A (en) * | 2017-03-23 | 2017-07-11 | 中国电子科技集团公司第三十八研究所 | A yard adjoint system is detectd in a kind of target collection |
| CN110727809A (en) * | 2019-09-27 | 2020-01-24 | 上海依图网络科技有限公司 | Face and mobile user identification code association query method and device and electronic equipment |
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