Information comparison method, device and terminal

Abstract

The present invention provides an information comparison method, device, and terminal. The method includes: obtaining a current facial image of a person to be identified, and generating facial images of each age group of the person to be identified based on the current facial image of the person to be identified; comparing the facial images of each age group of the person to be identified with facial images of lost persons of corresponding age groups in a lost persons database; if a first target lost person exists in the lost persons database, determining all first target lost persons as first-category similar persons to the person to be identified; if a second target lost person exists in the lost persons database, and the similarity between the facial image of the second target lost person's father or mother and the facial image of the corresponding age group of the person to be identified is greater than a third preset threshold, determining the second target lost person as a second-category similar person to the person to be identified. The present invention can improve the accuracy of information comparison and prevent the omission of similar persons.

Description

Technical Field

[0001] The present invention relates to the field of biometric identification technology, and in particular to an information comparison method, device and terminal. Background Art

[0002] The vagrant and begging management information system can manage the information of vagrants and beggars. The vagrant and begging management information system has a missing person database, which stores the relevant information of missing persons so as to facilitate the information comparison between vagrants and missing persons.

[0003] At present, the information comparison between homeless beggars and missing persons is only done by comparing the facial images of the homeless beggars with those of the missing persons. However, missing persons are usually lost in childhood, and the missing persons database only stores images of the missing persons as children, while the facial images of homeless beggars are usually images of adults. The accuracy of the information comparison between the two is poor. Summary of the Invention

[0004] Embodiments of the present invention provide an information comparison method, device, and terminal to solve the problem of poor accuracy in information comparison.

[0005] In a first aspect, an embodiment of the present invention provides an information comparison method, comprising:

[0006] Obtaining a current facial image of the person to be identified, and generating facial images of the person to be identified in various age groups based on the current facial image of the person to be identified;

[0007] Compare the facial images of the persons to be identified in each age group with the facial images of the missing persons in the missing persons database of the corresponding age groups;

[0008] If the first target missing person exists in the missing person database, all the first target missing persons are determined as first-category similar persons to the person to be identified; the similarity between the facial image of the first target missing person and the facial image of the corresponding age group of the person to be identified is greater than a first preset threshold;

[0009] If the second target missing person exists in the missing person database, a facial image of the second target missing person's father or mother is obtained, and the facial image of the second target missing person's father or mother is compared with a facial image of the corresponding age group of the person to be identified; the similarity between the facial image of the second target missing person and the facial image of the corresponding age group of the person to be identified is greater than a second preset threshold and not greater than a first preset threshold;

[0010] If the similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is greater than a third preset threshold, the second target missing person is determined as a second type of similar person to the person to be identified.

[0011] In a possible implementation, after comparing the facial image of the father or mother of the second target missing person with the facial images of the persons to be identified in the corresponding age group, the method further includes:

[0012] If the similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is not greater than the third preset threshold, the second target missing person is determined as a third type of similar person to the person to be identified.

[0013] In a possible implementation, the information comparison method further includes:

[0014] If a third target missing person exists in the missing person database, obtaining a facial image of the third target missing person's father or mother, and comparing the facial image of the third target missing person's father or mother with a facial image of the corresponding age group of the person to be identified; the similarity between the facial image of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than a fourth preset threshold and not greater than the second preset threshold;

[0015] If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than the fifth preset threshold, the third target missing person is determined as a fourth type of similar person to the person to be identified; the fifth preset threshold is greater than the third preset threshold.

[0016] In a possible implementation, after comparing the facial image of the father or mother of the third target missing person with the facial images of the persons to be identified in the corresponding age group, the method further includes:

[0017] If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than the third preset threshold and not greater than the fifth preset threshold, the third target missing person is determined to be a fifth type of similar person to the person to be identified;

[0018] If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is not greater than a third preset threshold, the third target missing person is determined as a dissimilar person to the person to be identified.

[0019] In a possible implementation, after determining the third target missing person as a fifth type of similar person to the person to be identified, the method further includes:

[0020] Sending the first category of similar persons, the second category of similar persons, the third category of similar persons, the fourth category of similar persons, and the fifth category of similar persons to a display terminal for display, and marking the similarity degree of each category of similar persons;

[0021] Among them, the similarity levels of the first category of similar persons, the second category of similar persons, the third category of similar persons, the fourth category of similar persons and the fifth category of similar persons decrease in sequence.

[0022] In one possible implementation, generating facial images of the person to be identified at various age groups based on the current facial image of the person to be identified includes:

[0023] The current facial image of the person to be identified is input into a preset image generation model to obtain facial images of the person to be identified in various age groups.

[0024] In a possible implementation, the information comparison method is applied to a homeless and begging management information system.

[0025] In a second aspect, an embodiment of the present invention provides an information comparison device, comprising:

[0026] An image generation module is used to obtain a current facial image of the person to be identified and generate facial images of the person to be identified of different age groups based on the current facial image of the person to be identified;

[0027] The first comparison module is used to compare the facial images of the persons to be identified in each age group with the facial images of the missing persons of the corresponding age groups in the missing persons database;

[0028] A first-category similar person determination module is configured to, if a first target missing person exists in the missing person database, determine all first target missing persons as first-category similar persons to the person to be identified; and the similarity between the facial image of the first target missing person and the facial image of the person to be identified in the corresponding age group is greater than a first preset threshold;

[0029] a second comparison module, configured to, if a second target missing person exists in the missing person database, obtain a facial image of the second target missing person's father or mother, and compare the facial image of the second target missing person's father or mother with a facial image of the person to be identified of a corresponding age group; wherein the similarity between the facial image of the second target missing person and the facial image of the person to be identified of the corresponding age group is greater than a second preset threshold and not greater than a first preset threshold;

[0030] The second-category similar person determination module is used to determine the second target missing person as a second-category similar person to the person to be identified if the similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is greater than a third preset threshold.

[0031] In a third aspect, an embodiment of the present invention provides a terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the information comparison method as described in the first aspect or any possible implementation of the first aspect are implemented.

[0032] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the information comparison method described in the first aspect or any possible implementation method of the first aspect.

[0033] An embodiment of the present invention provides an information comparison method, device and terminal. By generating facial images of various age groups of a person to be identified based on the current facial image of the person to be identified, and selecting facial images of the corresponding age groups of the person to be identified based on the age group of the lost person for comparison, the accuracy of the information comparison can be improved. In addition, for lost persons whose similarity is not very high, the facial image of the person to be identified is compared with the facial images of their parents, and whether they are similar persons is determined based on the comparison result, which can prevent the omission of similar persons to the person to be identified. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1 is a flowchart of an implementation of an information comparison method provided by an embodiment of the present invention;

[0036] Figure 2 is a schematic structural diagram of an information comparison device provided by an embodiment of the present invention;

[0037] Figure 3 is a schematic diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In the following description, specific details such as particular system structures and techniques are provided for purposes of illustration, not limitation, to facilitate a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0039] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below with reference to the accompanying drawings.

[0040] See also Figure 1 , which shows an implementation flow chart of the information comparison method provided by an embodiment of the present invention, wherein the execution subject of the information comparison method can be a terminal.

[0041] See also Figure 1 , the information comparison method is described in detail as follows:

[0042] In S101 , a current facial image of a person to be identified is acquired, and facial images of the person to be identified in various age groups are generated based on the current facial image of the person to be identified.

[0043] In some embodiments of the present invention, the information comparison method is applied to a homeless and begging management information system.

[0044] Wherein, the personnel to be identified can be the homeless beggars in the homeless beggars management information system. When entering the homeless beggars information in the homeless beggars management information system, the homeless beggars' facial images can be entered, and their names, ages, sex, fingerprint information, DNA information, etc. can also be entered.

[0045] In this embodiment, facial images of the person to be identified can be generated for various age groups based on the current facial image of the person to be identified. Age groups can be divided into pre-adulthood, post-adulthood to middle-aged, middle-aged, and elderly. Because the pre-adult age period undergoes significant changes, facial images of pre-adulthood individuals can be generated every three or five years, while facial images of individuals in other age groups can be generated every ten or twenty years. For example, age groups may include: 0-3 years old, 3-6 years old, 6-9 years old, 9-12 years old, 12-15 years old, 15-18 years old, 18-38 years old, 38-58 years old, 58-78 years old, 78-98 years old, etc.

[0046] In some embodiments of the present invention, generating facial images of the person to be identified at various age groups based on the current facial image of the person to be identified includes:

[0047] The current facial image of the person to be identified is input into a preset image generation model to obtain facial images of the person to be identified in various age groups.

[0048] The preset image generation model can be trained based on a face sample set. Specifically, adversarial training can be performed on the face sample set to obtain a discriminator and image generation model.

[0049] During training, the discriminator is used to determine whether the input face image is an image in the face sample set or an image generated by the picture generation model. Its input is a real face image in the face sample set and a face image generated by the picture generation model. When an age group is input, the output is the judgment result of whether the input image is a real sample.

[0050] The input of the image generation model is a real face image in the face sample set, and the output is a generated image under the input age range.

[0051] The image generation model can include an encoder and a generator. The encoder can project the input facial image into a corresponding feature space based on the input facial image and the corresponding age range. The generator can upsample the features of this feature space to generate a generated image for the corresponding age range.

[0052] In a possible implementation, before S102, the process further includes:

[0053] Before the comparison is performed, it is determined whether the face image to be compared is a frontal face image. If not, the image is rotated to a frontal face image.

[0054] The image to be compared can be used to locate both eyes; whether the eyes are level can be determined based on the located eyes. If the eyes are not level, the image to be compared can be rotated with the center of the located eyes as the base point until the eyes are level.

[0055] In S102 , the facial images of the persons to be identified in each age group are compared with the facial images of the missing persons in the corresponding age groups in the missing persons database.

[0056] According to the age group of the facial images of each missing person in the missing person database, the facial images of the person to be identified in that age group are selected for comparison to obtain the similarity between the two.

[0057] In S103, if there is a first target missing person in the missing person database, all first target missing persons are determined as the first category of similar persons to the person to be identified; the similarity between the facial image of the first target missing person and the facial image of the corresponding age group of the person to be identified is greater than a first preset threshold.

[0058] The first preset threshold is a relatively high similarity threshold, for example, it may be 90%, 95%, etc.

[0059] The similarity between the facial image of the first target missing person and the facial image of the corresponding age group of the person to be identified is greater than a first preset threshold, wherein the corresponding age group is the age group of the first target missing person.

[0060] The first target missing person is a person who has a relatively high similarity with the person to be identified, and is called the first type of similar person.

[0061] In S104, if the second target missing person exists in the missing person database, the facial image of the father or mother of the second target missing person is obtained, and the facial image of the father or mother of the second target missing person is compared with the facial image of the corresponding age group of the person to be identified; the similarity between the facial image of the second target missing person and the facial image of the corresponding age group of the person to be identified is greater than the second preset threshold and not greater than the first preset threshold.

[0062] The second preset threshold is smaller than the first preset threshold, for example, it may be 80%, 85%, etc.

[0063] For the second target missing person whose similarity is not as high as that of the first type of similar persons, the facial images of his / her father and / or mother can be compared with the facial images of the corresponding age group of the person to be identified. The corresponding age group is the age group of the father or mother of the second target missing person.

[0064] In S105, if the similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is greater than a third preset threshold, the second target missing person is determined as a second type of similar person to the person to be identified.

[0065] If the facial image of either the father or mother of the second target missing person has a similarity greater than a third preset threshold to the facial image of the corresponding age group of the person to be identified, the second target missing person is identified as a second-category similar person to the person to be identified. Since the comparison is with the parents, the third preset threshold can be set lower, for example, 60%, 50%, etc.

[0066] The embodiment of the present invention generates facial images of various age groups of the person to be identified based on the current facial image of the person to be identified, and selects facial images of the corresponding age groups of the person to be identified based on the age group of the lost person for comparison, thereby improving the accuracy of information comparison. In addition, for lost persons whose similarity is not very high, the facial image of the person to be identified is compared with the facial images of their parents, and whether they are similar persons is determined based on the comparison result, thereby preventing the omission of similar persons to the person to be identified.

[0067] In some embodiments of the present invention, after comparing the facial image of the father or mother of the second target missing person with the facial images of the corresponding age group of the person to be identified, the method further includes:

[0068] If the similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is not greater than the third preset threshold, the second target missing person is determined as a third type of similar person to the person to be identified.

[0069] If the similarity between the facial images of the father and mother of the second target missing person and the facial images of the corresponding age groups of the person to be identified is not greater than the third preset threshold, the second target missing person is determined to be a third type of similar person to the person to be identified.

[0070] In some embodiments of the present invention, the information comparison method further includes:

[0071] If a third target missing person exists in the missing person database, obtaining a facial image of the third target missing person's father or mother, and comparing the facial image of the third target missing person's father or mother with a facial image of the corresponding age group of the person to be identified; the similarity between the facial image of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than a fourth preset threshold and not greater than the second preset threshold;

[0072] If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than the fifth preset threshold, the third target missing person is determined as a fourth type of similar person to the person to be identified; the fifth preset threshold is greater than the third preset threshold.

[0073] For the third target missing person whose similarity is not as high as that of the second target missing person, if the similarity to either of their parents is high, they are determined to be the fourth type of similar person. The fifth preset threshold is greater than the third preset threshold, and the fifth preset threshold can be 65%, 55%, etc.

[0074] The fourth preset threshold is smaller than the second preset threshold, and the fourth preset threshold may be 70%, 75%, or the like.

[0075] In some embodiments of the present invention, after comparing the facial image of the father or mother of the third target missing person with the facial images of the persons to be identified of the corresponding age group, the method further includes:

[0076] If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than the third preset threshold and not greater than the fifth preset threshold, the third target missing person is determined to be a fifth type of similar person to the person to be identified;

[0077] If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is not greater than a third preset threshold, the third target missing person is determined as a dissimilar person to the person to be identified.

[0078] For the third target missing person whose similarity is not as high as the second target missing person, if the similarity to either of their parents is relatively high, they are determined to be the fifth category of similar persons. For the third target missing person whose similarity is not as high as the second target missing person, if the similarity to both of their parents is not high, they are determined to be dissimilar persons.

[0079] In a possible implementation, if the similarity between the facial image of the missing person and the facial image of the person to be identified in the corresponding age group is not greater than a fourth preset threshold, the missing person is determined to be a dissimilar person.

[0080] In some embodiments of the present invention, after determining the third target missing person as a fifth type of similar person to the person to be identified, the method further includes:

[0081] Sending the first category of similar persons, the second category of similar persons, the third category of similar persons, the fourth category of similar persons, and the fifth category of similar persons to a display terminal for display, and marking the similarity degree of each category of similar persons;

[0082] Among them, the similarity levels of the first category of similar persons, the second category of similar persons, the third category of similar persons, the fourth category of similar persons and the fifth category of similar persons decrease in sequence.

[0083] Different colors or corresponding text descriptions can be used to indicate the degree of similarity between different types of similar persons.

[0084] The similarity of the first category of similar persons is greater than that of the second category of similar persons; the similarity of the second category of similar persons is greater than that of the third category of similar persons; the similarity of the third category of similar persons is greater than that of the fourth category of similar persons; the similarity of the fourth category of similar persons is greater than that of the fifth category of similar persons.

[0085] The embodiment of the present invention can prevent omissions by dividing the data into several similarity levels, provide better references, and facilitate timely locating of missing persons.

[0086] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0087] The following are device embodiments of the present invention. For details not fully described therein, reference may be made to the corresponding method embodiments described above.

[0088] Figure 2 A schematic diagram of the structure of an information comparison device provided by an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, which are described in detail as follows:

[0089] like Figure 2 As shown, the information comparison device 30 includes: an image generation module 31 , a first comparison module 32 , a first type of similar person determination module 33 , a second comparison module 34 and a second type of similar person determination module 35 .

[0090] An image generation module 31 is used to obtain a current facial image of the person to be identified and generate facial images of the person to be identified of different age groups based on the current facial image of the person to be identified;

[0091] A first comparison module 32 is used to compare the facial images of the persons to be identified in each age group with the facial images of the missing persons in the missing persons database of the corresponding age groups;

[0092] A first-category similar person determination module 33 is configured to, if a first target missing person exists in the missing person database, determine all first target missing persons as first-category similar persons to the person to be identified; and the similarity between the facial image of the first target missing person and the facial image of the person to be identified in the corresponding age group is greater than a first preset threshold;

[0093] A second comparison module 34 is configured to, if a second target missing person exists in the missing person database, obtain a facial image of the second target missing person's father or mother, and compare the facial image of the second target missing person's father or mother with a facial image of the person to be identified of a corresponding age group; wherein the similarity between the facial image of the second target missing person and the facial image of the person to be identified of a corresponding age group is greater than a second preset threshold and not greater than a first preset threshold;

[0094] The second-category similar person determination module 35 is configured to determine the second-target missing person as a second-category similar person to the person to be identified if the similarity between the facial image of the father or mother of the second-target missing person and the facial image of the corresponding age group of the person to be identified is greater than a third preset threshold.

[0095] In a possible implementation, the information comparison device 30 further includes: a third type of similar person determination module.

[0096] The third category similar person determination module is used to determine the second target missing person as a third category similar person to the person to be identified if the similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is not greater than a third preset threshold.

[0097] In a possible implementation, the information comparison device 30 further includes: a fourth type of similar person determination module.

[0098] The fourth type of similar person identification module is used to:

[0099] If a third target missing person exists in the missing person database, obtaining a facial image of the third target missing person's father or mother, and comparing the facial image of the third target missing person's father or mother with a facial image of the corresponding age group of the person to be identified; the similarity between the facial image of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than a fourth preset threshold and not greater than the second preset threshold;

[0100] If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than the fifth preset threshold, the third target missing person is determined as a fourth type of similar person to the person to be identified; the fifth preset threshold is greater than the third preset threshold.

[0101] In a possible implementation, the information comparison device 30 further includes: a fifth category of similar persons determination module.

[0102] The fifth type of similar person identification module is used to:

[0103] If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than the third preset threshold and not greater than the fifth preset threshold, the third target missing person is determined to be a fifth type of similar person to the person to be identified;

[0104] If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is not greater than a third preset threshold, the third target missing person is determined as a dissimilar person to the person to be identified.

[0105] In a possible implementation, the information comparison device 30 further includes: a sending module.

[0106] The sending module is used to:

[0107] Sending the first category of similar persons, the second category of similar persons, the third category of similar persons, the fourth category of similar persons, and the fifth category of similar persons to a display terminal for display, and marking the similarity degree of each category of similar persons;

[0108] Among them, the similarity levels of the first category of similar persons, the second category of similar persons, the third category of similar persons, the fourth category of similar persons and the fifth category of similar persons decrease in sequence.

[0109] In a possible implementation, the image generation module 31 is further configured to:

[0110] The current facial image of the person to be identified is input into a preset image generation model to obtain facial images of the person to be identified in various age groups.

[0111] Figure 3 Schematic diagram of a terminal provided by an embodiment of the present invention. Figure 3 As shown, the terminal 4 of this embodiment includes: a processor 40, a memory 41, and a computer program 42 stored in the memory 41 and executable on the processor 40. When the processor 40 executes the computer program 42, the steps in the above-mentioned various information comparison method embodiments are implemented, such as Figure 1 Alternatively, when the processor 40 executes the computer program 42, the functions of the modules / units in the above-mentioned device embodiments are realized, for example, Figure 2 Functions of the modules / units 31 to 35 are shown.

[0112] Exemplarily, the computer program 42 may be divided into one or more modules / units, which are stored in the memory 41 and executed by the processor 40 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program 42 in the terminal 4. For example, the computer program 42 may be divided into Figure 2 Modules / units 31 to 32 are shown.

[0113] The terminal 4 may include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will understand that Figure 3 It is only an example of terminal 4 and does not constitute a limitation on terminal 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0114] The processor 40 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0115] The memory 41 may be an internal storage unit of the terminal 4, such as a hard disk or memory of the terminal 4. The memory 41 may also be an external storage device of the terminal 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash memory card, etc. equipped on the terminal 4. Furthermore, the memory 41 may include both an internal storage unit of the terminal 4 and an external storage device. The memory 41 is used to store the computer program and other programs and data required by the terminal. The memory 41 may also be used to temporarily store data that has been output or is about to be output.

[0116] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0117] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0118] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0119] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, and can be electrical, mechanical, or other forms.

[0120] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0121] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0122] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above-mentioned various information comparison method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media does not include electric carrier signals and telecommunication signals.

[0123] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. An information comparison method, characterized in that: include: Acquire a current facial image of the person to be identified, and generate facial images of the person to be identified in various age groups based on the current facial image of the person to be identified; Comparing the facial images of the persons to be identified in each age group with the facial images of the missing persons in the missing persons database of the corresponding age groups; If a first target missing person exists in the missing person database, all the first target missing persons are determined as first-category similar persons to the person to be identified; and the similarity between the facial image of the first target missing person and the facial image of the person to be identified in the corresponding age group is greater than a first preset threshold; If a second target missing person exists in the missing person database, obtaining a facial image of the second target missing person's father or mother, and comparing the facial image of the second target missing person's father or mother with a facial image of the corresponding age group of the person to be identified; the similarity between the facial image of the second target missing person and the facial image of the corresponding age group of the person to be identified is greater than a second preset threshold and not greater than the first preset threshold; If the similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is greater than a third preset threshold, the second target missing person is determined as a second type of similar person to the person to be identified; If the similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is not greater than a third preset threshold, the second target missing person is determined to be a third type of similar person to the person to be identified; If a third target missing person exists in the missing person database, obtaining a facial image of the father or mother of the third target missing person, and comparing the facial image of the father or mother of the third target missing person with a facial image of the corresponding age group of the person to be identified; the similarity between the facial image of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than a fourth preset threshold and not greater than the second preset threshold; If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than a fifth preset threshold, the third target missing person is determined to be a fourth type of similar person to the person to be identified; the fifth preset threshold is greater than the third preset threshold; If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than the third preset threshold and not greater than the fifth preset threshold, the third target missing person is determined to be a fifth type of similar person to the person to be identified; If the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is not greater than the third preset threshold, the third target missing person is determined as a dissimilar person to the person to be identified.

2. The information comparison method according to claim 1, characterized in that: After determining the third target missing person as a fifth type of similar person to the person to be identified, the method further includes: sending the first category of similar persons, the second category of similar persons, the third category of similar persons, the fourth category of similar persons, and the fifth category of similar persons to a display terminal for display, and marking the degree of similarity of each category of similar persons; Among them, the similarity levels of the first category of similar persons, the second category of similar persons, the third category of similar persons, the fourth category of similar persons and the fifth category of similar persons decrease in sequence.

3. The information comparison method according to any one of claims 1 to 2, characterized in that: The step of generating facial images of the person to be identified of various age groups based on the current facial image of the person to be identified includes: The current facial image of the person to be identified is input into a preset image generation model to obtain facial images of the person to be identified in various age groups.

4. The information comparison method according to any one of claims 1 to 2, characterized in that: The information comparison method is applied to a homeless and begging management information system.

5. An information comparison device, characterized in that: include: An image generation module is used to obtain a current facial image of a person to be identified, and generate facial images of the person to be identified of various age groups based on the current facial image of the person to be identified; A first comparison module is used to compare the facial images of the persons to be identified in each age group with the facial images of the missing persons of the corresponding age groups in the missing persons database; A first-category similar person determination module is configured to, if a first target missing person exists in the missing person database, determine all first target missing persons as first-category similar persons to the person to be identified; and the similarity between the facial image of the first target missing person and the facial image of the person to be identified in the corresponding age group is greater than a first preset threshold; a second comparison module, configured to, if a second target missing person exists in the missing person database, obtain a facial image of the second target missing person's father or mother, and compare the facial image of the second target missing person's father or mother with a facial image of the corresponding age group of the person to be identified; wherein the similarity between the facial image of the second target missing person and the facial image of the corresponding age group of the person to be identified is greater than a second preset threshold and not greater than the first preset threshold; a second-category similar person determination module, configured to determine the second target missing person as a second-category similar person to the person to be identified if the degree of similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is greater than a third preset threshold; a third-category similar person determination module, configured to determine the second target missing person as a third-category similar person to the person to be identified if the degree of similarity between the facial image of the father or mother of the second target missing person and the facial image of the corresponding age group of the person to be identified is not greater than a third preset threshold; a fourth category similar person determination module, configured to, if a third target missing person exists in the missing person database, obtain a facial image of the third target missing person's father or mother, and compare the facial image of the third target missing person's father or mother with facial images of persons in the corresponding age group of the person to be identified; if the similarity between the facial image of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than a fourth preset threshold and not greater than the second preset threshold; if the similarity between the facial image of the third target missing person's father or mother and the facial image of the corresponding age group of the person to be identified is greater than a fifth preset threshold, determine the third target missing person as a fourth category similar person to the person to be identified; and if the fifth preset threshold is greater than the third preset threshold; The fifth category similar person determination module is used to determine the third target missing person as a fifth category similar person to the person to be identified if the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is greater than the third preset threshold and not greater than the fifth preset threshold; and to determine the third target missing person as a dissimilar person to the person to be identified if the similarity between the facial image of the father or mother of the third target missing person and the facial image of the corresponding age group of the person to be identified is not greater than the third preset threshold.

6. A terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the information comparison method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the information comparison method according to any one of claims 1 to 4 are implemented.

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