Trace material evidence analysis method and device and storage medium
By using Pearson's correlation coefficient model and detection equipment information in trace evidence identification, the problem of misjudgment of trace evidence identification in the prior art is solved, and a more accurate determination of evidence source is achieved.
Patent Information
- Application Number
- CN202411529478.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-30
- Publication Date
- 2025-03-25
AI Technical Summary
In the prior art, the spectral identification of trace evidence is easily affected by differences in detection equipment and on-site environmental factors, resulting in misjudgment of identification.
By obtaining the optical map of the evidence, search for relevant standard maps in the preset database based on the Pearson correlation coefficient model, combine the detection equipment information and the survey material number, determine the source information of the evidence, and store it in the form of a data point table for subsequent comparison.
It improves the accuracy of trace evidence identification, reduces the possibility of misjudgment of identification, and ensures that identification experts can make judgments based on more reliable data.
Smart Images
Figure CN119691190A_ABST
Abstract
Description
Technical Field
[0001] This document relates to the field of forensic science, and more particularly to a method, device and storage medium for analyzing trace evidence. Background Art
[0002] Trace evidence is a tiny material that can prove the true situation of a case. These trace evidences often become a breakthrough in case investigation and detection, playing a key role in evidence. How to determine the types of trace evidence has become a focus of attention.
[0003] In the prior art, the spectrum of the trace substance is first obtained, and then the identification expert determines the type of the trace substance based on the spectrum.
[0004] However, external factors such as differences in testing equipment and on-site environment can affect the shape of the map, thereby affecting the judgment of the identification experts and may cause them to misjudge. Summary of the invention
[0005] In view of the above analysis, the present application aims to propose a trace evidence analysis method, device and storage medium to assist identification experts in making accurate judgments.
[0006] In a first aspect, one or more embodiments of this specification provide a method for analyzing trace evidence, comprising:
[0007] Obtaining an optical spectrum of the evidence and the type of the optical spectrum;
[0008] According to the optical spectrum of the evidence and the type of the optical spectrum, searching a preset first database for a standard spectrum related to the optical spectrum of the evidence; and
[0009] The source information of the evidence is determined based on the standard spectrum, the sample number corresponding to the standard spectrum and the detection equipment information, wherein the sample number of the standard spectrum and the standard spectrum are stored correspondingly in the first database, and the detection equipment information of the standard spectrum and the standard spectrum are stored correspondingly.
[0010] Furthermore, the method further comprises:
[0011] Receiving the standard atlas;
[0012] Determine the sample number, source information, testing equipment information and spectrum type of the standard spectrum; and
[0013] The standard spectrum and the sample number, detection equipment information, source information and spectrum type of the standard spectrum are stored in the first database in the form of a data point table.
[0014] Furthermore, searching for a standard spectrum related to the optical spectrum of the evidence includes:
[0015] Calculating the correlation coefficient between the optical spectrum and each spectrum stored in the first database based on the Pearson correlation coefficient model; and
[0016] The spectrum whose correlation coefficient exceeds a preset threshold is determined to be a standard spectrum related to the optical spectrum of the evidence.
[0017] Furthermore, the method further comprises:
[0018] Receive external input of graph selection instructions;
[0019] According to the spectrum selection instruction, a plurality of standard spectra are selected from the first database; and
[0020] The optical spectrum of the evidence and the multiple standard spectra are compared in pairs to obtain a similarity comparison table.
[0021] Furthermore, the method further comprises:
[0022] Obtaining the sample number from the first database;
[0023] According to the sample number, the source information of the evidence is searched in a preset second preset database.
[0024] In a second aspect, one or more embodiments of this specification provide a trace evidence analysis device, including: an acquisition module, a spectrum matching module, a spectrum determination module, and a first database;
[0025] The acquisition module is used to acquire the optical spectrum of the evidence and the type of the optical spectrum;
[0026] The pattern matching module is used to determine, in the first database, a standard pattern related to the optical pattern of the evidence according to the optical pattern of the evidence and the type of the optical pattern; and
[0027] The spectrum determination module is used to determine the source information of the evidence according to the standard spectrum, the sample number corresponding to the standard spectrum and the detection equipment information;
[0028] The sample number of the standard spectrum in the first database and the standard spectrum are stored correspondingly, and the detection equipment information of the standard spectrum and the standard spectrum are stored correspondingly.
[0029] Furthermore, the device also includes a data processing module;
[0030] The data processing module is used to receive the standard spectrum; determine the sample number, source information and spectrum type of the standard spectrum; and store the standard spectrum and the sample number, source information and spectrum type of the standard spectrum in the first database in the form of a data point table.
[0031] Furthermore, the spectrum matching module is used to determine the correlation coefficient between the optical spectrum and each spectrum stored in the first database based on a Pearson correlation coefficient model; and determine that the spectrum whose correlation coefficient exceeds a preset threshold is a standard spectrum related to the optical spectrum of the evidence.
[0032] Furthermore, the device also includes: a multi-atlas comparison module;
[0033] The multi-spectrum comparison module is used to receive a spectrum selection instruction input from the outside; select multiple standard spectra from the first database according to the spectrum selection instruction; and compare the optical spectrum of the evidence with the multiple standard spectra in pairs to obtain a similarity comparison table.
[0034] In a third aspect, one or more embodiments of the present specification provide a storage medium for storing computer-executable instructions, characterized in that when the computer-executable instructions are executed, the steps of the training method applied to the time-domain convolutional network model described in any one of the first aspects are implemented.
[0035] Compared with the prior art, this application can at least achieve the following technical effects:
[0036] The spectrum can be regarded as a curve of the signal changing continuously over time, that is, the data in the spectrum is composed of continuous data points. Based on the characteristics of the spectrum, it is chosen to store the spectrum in the form of a data point graph, so as to realize the digitization of the spectrum in an appropriate manner, laying a technical foundation for the subsequent comparison of spectra. At the same time, the introduction of detection equipment information and sample numbers in the database makes it easier for identification experts to include equipment information in the evaluation scope during the identification process, and helps identification experts to accurately determine the source information of the evidence through the sample number. In summary, this application can assist identification experts to complete the identification comprehensively and accurately. BRIEF DESCRIPTION OF THE DRAWINGS
[0037] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.
[0038] Figure 1A flow chart of a trace evidence analysis method provided for one or more embodiments of this specification;
[0039] Figure 2 An implementation provided for one or more embodiments of this specification Figure 1 A schematic diagram of the structure of the device of the method;
[0040] Figure 3 A schematic diagram of the structure of a trace evidence analysis device provided for one or more embodiments of this specification. DETAILED DESCRIPTION
[0041] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the following will be combined with the drawings in one or more embodiments of this specification to clearly and completely describe the technical solutions in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.
[0042] The identification process of trace evidence: First, the collected trace evidence is tested to obtain the corresponding spectrum. Then the identification expert identifies the trace evidence based on the spectrum. Therefore, how the test results are reflected in the subsequent identification process has an important impact on the identification results.
[0043] Therefore, in order to allow the test results to be better expressed in the subsequent identification process, the present application embodiment provides a method for analyzing trace evidence, such as Figure 1 As shown, the following steps are included:
[0044] Step 1: Obtain the optical spectrum of the evidence and the type of the optical spectrum.
[0045] In the embodiment of the present application, the optical spectrum includes: infrared, ultraviolet, Raman or other spectrum. The type of the corresponding optical spectrum is infrared, ultraviolet, Raman or other spectrum. The detection equipment information may include: the identification, model, detection accuracy, applicable conditions, etc. of the detection equipment.
[0046] Step 2: Based on the optical spectrum of the evidence and the type of the optical spectrum, a standard spectrum related to the optical spectrum of the evidence is searched in a preset first database.
[0047] In the embodiment of the present application, by traversing the same type of optical spectra in the database, a standard spectrum related to the optical spectrum of the evidence is determined. Among them, the standard spectrum includes: spectra derived from public resource spectra, spectra obtained by analyzing standard substances, spectra of samples in actual cases, and spectra detected during scientific research analysis.
[0048] For example, if the spectrum of the evidence is an infrared spectrum, all infrared spectra in the database are traversed to determine a standard spectrum related to the optical spectrum of the evidence.
[0049] Step 3: Determine the source information of the evidence based on the testing equipment information, the standard spectrum and the sample number corresponding to the standard spectrum.
[0050] In the embodiment of the present application, the sample number and the standard spectrum of the standard spectrum are stored correspondingly in the database, and the detection equipment information and the standard spectrum of the standard spectrum are stored correspondingly.
[0051] For trace evidence, the crime scene environment is ever-changing. For example, wet, dry, underwater, muddy, hot, cold, etc. In such a changing environment, the spectra of the same trace evidence will show diversity. Different detection equipment will have better detection effects on trace evidence in a certain environment due to design concepts or detection methods. Therefore, providing detection equipment information can provide more clues for identification experts.
[0052] The first level of the sample number consists of three digits, indicating the type of the test fixture; the second level consists of five digits, indicating the serial number of the test fixture. This numbering method ensures that the number of each test fixture is unique and non-repetitive, and even if the test fixture is scrapped, the number cannot be used again. Based on the characteristics of the sample number, in order to improve the accuracy of identification and facilitate data comparison, a sample number is set for each spectrum.
[0053] Based on the above scheme, it can be known that different detection equipment may have an impact on the detection results. In order to reflect this impact in the subsequent identification process. In the embodiment of the present application, the specific process of constructing the first database is:
[0054] Receive standard atlas;
[0055] Determine the sample number, source information and map type of the standard map; and
[0056] The standard spectrum and the sample number, source information and spectrum type of the standard spectrum are stored in the first database in the form of a data point table.
[0057] It should be noted that the source information refers to the source of the trace evidence corresponding to the standard spectrum. For example, if the trace evidence is a fiber, the fiber can come from clothing, bedding and other objects that may contain fibers, and the objects containing fibers are the source of the fiber. Since the spectrum lines in the spectrum are functions of the light signal changing over time, the spectrum lines in the spectrum can be regarded as lines composed of multiple data points. And because these data points have specific meanings, it is not possible to only compare the shapes of the spectrum lines in a feature extraction manner. Taking the above factors into consideration, the present application chooses to store in the form of a data point table, so that each data point can be compared when comparing the spectrum later, thereby realizing the consideration of the impact of different devices on the test results into the subsequent identification process.
[0058] In an embodiment of the present application, based on the storage form of the spectrum, the Pearson correlation coefficient model is selected to evaluate the similarity between spectra. Specifically, based on the Pearson correlation coefficient model, the correlation coefficient of the optical spectrum and each spectrum stored in the first database is determined. The spectrum whose correlation coefficient exceeds the preset threshold is determined to be a standard spectrum related to the optical spectrum of the evidence. That is, by comparing the correlation coefficient, a spectrum similar to trace evidence is selected from the first database. Among them, the Pearson correlation coefficient model is specifically defined as follows: the pearson correlation coefficient P(x,y) of two continuous variables (X,Y) is equal to the covariance cov(X,Y) between them divided by the product of their respective standard deviations (σX,σY). The value of the coefficient is always between -1.0 and 1.0, and variables close to 0 are called uncorrelated, and variables close to 1 or -1 are called strongly correlated. That is, P=PEARSON(X,Y), and this method uses the square of P as the matching degree for calculation and analysis.
[0059] In the embodiment of the present application, during the identification process, the identification expert believes that there are multiple possibilities for trace evidence based on the spectra. At this time, it is necessary to call multiple spectra for pairwise comparison in order to eliminate some options. Specifically,
[0060] Receive external input of graph selection instructions;
[0061] According to the spectrum selection instruction, multiple standard spectra are selected from the first database;
[0062] The optical spectrum of the evidence and multiple standard spectra are compared two by two to obtain a similarity comparison table, as shown in Table 1.
[0063] Table 1 Similarity comparison table
[0064] Figure 1 Figure 2 Figure 3 Figure 4 Figure 1 1 m n p Figure 2 m 1 q r Figure 3 n q 1 s Figure 4 p r s 1
[0065] Among them, m, n, p, q and r represent similarity.
[0066] Based on Table 1, identification experts can exclude the least relevant spectra among spectra 1-4, thereby narrowing the scope of investigation.
[0067] In the embodiment of the present application, the sample number represents the source of the trace evidence, but the information of its source is usually stored in a special database (second database), which may not be in the first database. Therefore, preferably, after determining the sample number corresponding to the spectrum, the source information of the evidence is searched in the preset second preset database according to the sample number.
[0068] In order to illustrate the feasibility of the above embodiments, this application gives the following specific examples:
[0069] like Figure 2 As shown, execute Figure 1 The system of the method includes two databases, database 1 stores the spectra to be identified, and database 2 stores the standard spectra in the form of data point tables. During identification, the identification expert retrieves the spectra to be identified from database 1 on the terminal device to form a list of spectra to be identified.
[0070] When an identification expert wants to identify a to-be-identified spectrum in the list, the identification expert can set a correlation coefficient threshold through the terminal device to filter the standard spectrum to be displayed. The terminal device returns the standard spectrum to be displayed in the form of a list.
[0071] When the terminal device displays the standard atlas, if the identification expert wants to further narrow the scope, he can compare two by two based on the list of standard atlases to obtain a similarity comparison table, or compare any two or more atlases in the list.
[0072] like Figure 3 As shown, the embodiment of the present application provides a trace evidence analysis device, including: an acquisition module 301, a spectrum matching module 302, a spectrum determination module 303 and a first database 304;
[0073] The acquisition module 301 is used to acquire the optical spectrum of the evidence and the type of the optical spectrum;
[0074] The pattern matching module 302 is used to determine a standard pattern related to the optical pattern of the evidence in the first database according to the optical pattern of the evidence and the type of the optical pattern; and
[0075] The spectrum determination module 303 is used to determine the source information of the evidence according to the standard spectrum, the sample number corresponding to the standard spectrum and the detection equipment information;
[0076] In the first database 304, the sample number of the standard spectrum and the standard spectrum are stored correspondingly, and the detection equipment information of the standard spectrum and the standard spectrum are stored correspondingly.
[0077] In the embodiment of the present application, the device further includes a data processing module;
[0078] The data processing module is used to receive the standard spectrum; determine the sample number, source information and spectrum type of the standard spectrum; and store the standard spectrum and the sample number, source information and spectrum type of the standard spectrum in the first database in the form of a data point table.
[0079] In the embodiment of the present application, the spectrum matching module 302 is used to determine the correlation coefficient between the optical spectrum and each spectrum stored in the first database based on the Pearson correlation coefficient model; and determine that the spectrum whose correlation coefficient exceeds a preset threshold is a standard spectrum related to the optical spectrum of the evidence.
[0080] In the embodiment of the present application, the device further comprises: a multi-atlas comparison module;
[0081] The multi-spectrum comparison module is used to receive a spectrum selection instruction input from the outside; select multiple standard spectra from the first database according to the spectrum selection instruction; and compare the optical spectrum of the evidence with the multiple standard spectra in pairs to obtain a similarity comparison table.
[0082] It should be noted that the embodiments of the storage medium in this specification and the embodiments of the blockchain-based service provision method in this specification are based on the same inventive concept. Therefore, the specific implementation of this embodiment can refer to the aforementioned corresponding implementation of the blockchain-based service provision method, and the repeated parts will not be repeated.
[0083] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0084] In the 1930s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method flow). However, with the development of technology, many improvements to the method flow today can be regarded as direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.
[0085] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.
[0086] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
[0087] For the convenience of description, the above devices are described in terms of functions and are divided into various units. Of course, when implementing the embodiments of this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.
[0088] It should be understood by those skilled in the art that one or more embodiments of this specification may be provided as a method, system or computer program product. Therefore, one or more embodiments of this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0089] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0090] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0091] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0092] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.
[0093] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.
[0094] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.
[0095] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.
[0096] One or more embodiments of the present specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. One or more embodiments of the present specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.
[0097] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.
[0098] The above description is only an embodiment of this document and is not intended to limit this document. For those skilled in the art, this document may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this document should be included in the scope of the claims of this document.
Claims
1. A method for analyzing trace evidence, characterized in that: include: Obtaining an optical spectrum of the evidence and the type of the optical spectrum; According to the optical spectrum of the evidence and the type of the optical spectrum, searching a preset first database for a standard spectrum related to the optical spectrum of the evidence; and The source information of the evidence is determined based on the standard spectrum, the sample number corresponding to the standard spectrum and the detection equipment information, wherein the sample number of the standard spectrum and the standard spectrum are stored correspondingly in the first database, and the detection equipment information of the standard spectrum and the standard spectrum are stored correspondingly.
2. The method according to claim 1, characterized in that The method further comprises: Receiving the standard atlas; Determine the sample number, source information, testing equipment information and spectrum type of the standard spectrum; and The standard spectrum and the sample number, detection equipment information, source information and spectrum type of the standard spectrum are stored in the first database in the form of a data point table.
3. The method according to claim 2, characterized in that The standard patterns that are searched for in relation to the optical pattern of the evidence include: Calculating the correlation coefficient between the optical spectrum and each spectrum stored in the first database based on the Pearson correlation coefficient model; and The spectrum whose correlation coefficient exceeds a preset threshold is determined to be a standard spectrum related to the optical spectrum of the evidence.
4. The method according to claim 1, characterized in that: The method further comprises: Receive external input of graph selection instructions; According to the spectrum selection instruction, a plurality of standard spectra are selected from the first database; and The optical spectrum of the evidence and the plurality of standard spectra are compared in pairs to obtain a similarity comparison table.
5. The method according to claim 1, characterized in that The method further comprises: Obtaining the sample number from the first database; According to the sample number, the source information of the evidence is searched in a preset second database.
6. A trace evidence analysis device, characterized in that: include: An acquisition module, a graph matching module, a graph determination module and a first database; The acquisition module is used to acquire the optical spectrum of the evidence and the type of the optical spectrum; The pattern matching module is used to search the first database for a standard pattern related to the optical pattern of the evidence according to the optical pattern of the evidence and the type of the optical pattern; The spectrum determination module is used to determine the source information of the evidence according to the standard spectrum, the sample number corresponding to the standard spectrum and the detection equipment information; and The sample number of the standard spectrum in the first database and the standard spectrum are stored correspondingly, and the detection equipment information of the standard spectrum and the standard spectrum are stored correspondingly.
7. The device according to claim 6, characterized in that The device also includes a data processing module; The data processing module is used to receive the standard spectrum; determine the sample number, source information, detection equipment information and spectrum type of the standard spectrum; and store the standard spectrum and the sample number, source information, detection equipment information and spectrum type of the standard spectrum in the form of a data point table in the first database.
8. The device according to claim 7, characterized in that The spectrum matching module is used to determine the correlation coefficient between the optical spectrum and each spectrum stored in the first database based on the Pearson correlation coefficient model; and determine that the spectrum whose correlation coefficient exceeds a preset threshold is a standard spectrum related to the optical spectrum of the evidence.
9. The device according to claim 6, characterized in that The device also includes: a multi-atlas comparison module; The multi-spectrum comparison module is used to receive a spectrum selection instruction input from the outside; select multiple standard spectra from the first database according to the spectrum selection instruction; and compare the optical spectrum of the evidence with the multiple standard spectra in pairs to obtain a similarity comparison table.
10. A storage medium for storing computer executable instructions, characterized in that: When the computer executable instructions are executed, the steps of a trace evidence analysis method according to any one of claims 1 to 5 are implemented.