CN112487863A - Fingerprint extraction and identification system and method based on fluorescent material - Google Patents
Fingerprint extraction and identification system and method based on fluorescent material Download PDFInfo
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Abstract
The invention discloses a fingerprint extraction and identification system and method based on fluorescent materials. The system comprises a fingerprint library, a handheld terminal and a fingerprint extraction and analysis module; the handheld terminal comprises a light source control panel, an excitation light source module, a macro lens and a smart phone camera; a fingerprint feature extraction algorithm and a fingerprint feature comparison algorithm are built in the fingerprint analysis module; the fingerprint identification method integrates the functions of fluorescence excitation, fingerprint image acquisition, fingerprint extraction and identification, has the characteristics of convenience in carrying, high timeliness, simplicity and convenience in operation, no need of multi-person cooperation and the like, and is suitable for the technical field of on-site trace detection.
Description
Technical Field
The invention belongs to the technical field of on-site trace inspection, and particularly relates to a fingerprint extraction and identification system and method based on a fluorescent material.
Background
Fingerprint identification has been widely used in criminal site investigation as a relatively accurate technique for identifying a target person by comparing feature point information of different fingerprints for a long time. In-situ fingerprint identification techniques typically require two steps: fingerprint extraction and fingerprint identification, wherein the fingerprint extraction completes the imaging and extraction of fingerprint information, and the fingerprint identification performs fingerprint comparison and suspect target confirmation by comparing the characteristic points of the fingerprint image with a fingerprint library. At present, common fingerprint extraction methods are powder visualization (lubricating index, Pear G.Schunenn, and Derrick T.Reid.white powder visualization using branched and coherent light in the molecular fingerprint region, Optics Express,2018,26(19):25364 2525369), fumigation (J Almog, Y Sasson, A Analysis chemical reagents for the differentiation of molecular fingerprints, 2-guided adaptation of water vapor deposition fuels-a solution to the imaging reagent, Journal of research, 1979,24(2):431 436), silver nitrate (F.M.Kerrick, A.D.infiltration. moisture Analysis of the coating reagent, Journal of Analysis, 1979,24(2):431 436), silver nitrate (F.M.Kerrick, see batch of Laser, balance, 2. filtration of Laser, 1. reflection of Laser, reflection of silver nitrate, see 1. balance, 1. reflection of Laser, reflection of silver nitrate, reflection of, 1983,38(10): 1347-.
At present, when the fingerprint photographic extraction technology based on fluorescent powder is applied, multiple persons are generally required to cooperate, and fingerprint extraction is completed through the mutual cooperation of an excitation light source and a camera. The open environment and the cooperation of multiple persons not only lead to the complexity of steps in the fingerprint extraction process, but also have more influence factors, such as different angles, light and shadow changes in the environment, the stability of handheld equipment and the like, so that the difference of the definition of an image extracted by the fingerprint is larger, and the accuracy of fingerprint identification and authentication is seriously influenced. Meanwhile, the result of the fingerprint extraction needs to be transmitted to a background to be identified by using the fingerprint, namely, the fingerprint needs to be displayed, the picture is taken, and the fingerprint identification comparison is carried out (Mengshanhan, Tianhualin, application and analysis of fingerprint inspection in criminal investigation work, scientific Chinese people, 2016 and 20).
In recent years, fingerprint analysis and identification technology has been rapidly developed as an important artificial intelligence algorithm technology capable of providing security and public security, and has been widely applied to various occasions and various mobile devices (Bang Wang, qiyun Chen, Laurence t.yang, Han-chip chao.inor smartphone localization: springs and approaches, IEEE Transactions on Multimedia,2016,23(3): 82-89).
Disclosure of Invention
The invention provides a fingerprint extraction and identification system and method based on a fluorescent material, aiming at the problems of expensive cost, inconvenience in carrying, complex flow, poor detection timeliness, no support for real-time analysis and the like of the conventional fingerprint extraction system and method.
The purpose of the invention is realized by at least one of the following technical solutions.
A fingerprint extraction and identification system based on fluorescent materials comprises a fingerprint library, a handheld terminal and a fingerprint extraction and analysis module;
the handheld terminal comprises a light source control panel, an excitation light source module, a macro lens and a smart phone camera;
a fingerprint feature extraction algorithm and a fingerprint feature comparison algorithm are built in the fingerprint analysis module;
an operator places a fingerprint in a sampling area of the handheld terminal, the fingerprint analysis module operates a fingerprint feature extraction algorithm to call the handheld terminal to extract fingerprint feature information, and then operates a fingerprint feature comparison algorithm to compare the extracted fingerprint feature information with information in a fingerprint library, so that fingerprint identification is realized.
Further, before fingerprint extraction, fingerprint imaging magnetic powder made of fluorescent luminescent materials is brushed and displayed on the fingerprint, and redundant powder on the surface is absorbed, so that fingerprint lines can be clearly displayed;
the fingerprint extraction and analysis module and the fingerprint camera imaging are both realized through a smart phone, wherein the fingerprint extraction and analysis module is carried in an android environment to operate, and the camera is a camera in the smart phone and is matched with a macro lens to observe fingerprint imaging so as to extract fingerprint characteristics.
Further, the excitation light source module comprises a fluorescence excitation light source module and a white light excitation light source module, and is used for realizing fingerprint imaging of the fingerprint powder to be brushed under different fingerprint extraction conditions, and the fluorescence excitation light source module is an ultraviolet light source and is used for providing excitation light with uniform irradiation light spots in a fingerprint acquisition area; the white light excitation light source module is used for providing white light with uniform light intensity and illuminating light spots, and the fingerprints are directly imaged under a light-colored background.
Further, when the fingerprint feature extraction algorithm runs, a smart phone camera is called to shoot, an excitation light source module is switched through a light source control board under different fingerprint extraction conditions, light intensity change is controlled to excite a fluorescent material, clear image amplification is completed through a macro lens in a handheld terminal, clear fingerprint imaging is achieved, a proper fingerprint acquisition area is selected, image preprocessing is performed, and fingerprint features are extracted;
the information in the fingerprint database is fingerprint characteristic information which is extracted in advance through a fingerprint characteristic extraction algorithm or is directly imported and stored in the smart phone.
Further, the image preprocessing is to remove the interference of uneven brightness and other noises in the fingerprint image by a series of processing on the original collected fingerprint image, and restore the line information of the real image by line thinning and repairing, and specifically comprises the following steps:
carrying out gray level processing on the acquired image, and carrying out image gray level normalization processing by adopting a self-adaptive local binarization image separation method; fingerprint image enhancement is carried out; carrying out image background segmentation to remove noise interference in the fingerprint as much as possible; searching a maximum gray value in the image as an initial value according to the sequence; calculating a direction value or ridge frequency to carry out local Gabor filtering; determining the next point of ridge line tracking; and comparing the data, judging whether the end condition is met or not according to a preset threshold, if so, returning to the starting point for direction tracking, and if the reverse tracking is finished, searching the maximum gray value again for other point analysis until the whole fingerprint image is traversed.
Further, the image gray scale normalization processing is to perform image processing by adopting a local mean method in an adaptive local binarization method, divide the fingerprint image into image blocks which are not overlapped and have uniform sizes, and calculate the variance of each block according to the gray scale of the image block: the gray scale of the image block is obtained by calculating the mean value of the gray scale values in the image block; the gray value variance of the image block is obtained by the mean value of the pixel gray value and the average gray value in the image block; setting a threshold value for the variance, comparing the variance with the threshold value, and separating the background from the fingerprint ridge area. The method is realized on the basis that the variance of a background area is small, and the variance of a fingerprint area is large due to ridge and valley structures, and if the variance of a certain image block is not zero or has a large difference with a threshold, the area is further subjected to threshold segmentation; the mean variance algorithm is specifically as follows:
the size of the fingerprint image is m multiplied by m, the fingerprint image is divided into image blocks which are not overlapped with each other and have uniform size, and the size of each block is n multiplied by n; in the fingerprint image, the abscissa and ordinate positions of an image block in the fingerprint image are indicated (i, j), and the coordinate positions of pixels in the image block are indicated (u, v);
the sum of the gray values of the points in the image block is calculated according to the following formula:
wherein L (u, v) is a pixel gray scale value in an image block, M (i, j) is a gray scale sum of an image block of the (i, j) th block, i is 1, 2 … k, j is 1, 2 … k, and k is M/n;
the gray variance of the image block is:
a (i, j) is the mean value of the gray values in the image blocks of the (i, j), and an effective fingerprint area and a background area can be judged by setting a threshold value of V (i, j);
selecting threshold value TdIf V (i, j)>TdIf the value of the corresponding image block in the image block (i, j) is set to F (i, j) ═ 1, then the area where the image block is located is an effective fingerprint area block; otherwise, the value of the image block is set to F (i, j) ═ 0, and the image block is a background region block.
Furthermore, the light source control panel comprises a light source switch, a light intensity control function, a light source switching function and a charging function, the switching of the ultraviolet light source and the white light source under different environments can be realized, the use of equipment under different environments is facilitated, the charging function can be realized by the built-in battery, the equipment can be conveniently used at any time, and the display of the power state lamp is normally on when the power state lamp is turned on.
Further, the macro lens and the smart phone camera are sequentially arranged right above the fingerprint acquisition area; the fluorescence excitation light source module and the white light excitation light source module are symmetrically distributed at the front and the back of the two sides of the macro lens, have the same height and are sequentially and closely arranged; the macro lens and the optical axis of the smart phone camera form an included angle of 45 degrees with the central optical axes of the fluorescence excitation light source module and the white light excitation light source module.
Further, the fingerprint imaging collection can be carried out on the site fingerprint by using a white light source module or a fluorescence excitation light source module according to the requirement; under a complex background, the fluorescent material is excited through the fluorescence excitation light source module, fingerprint highlight is realized, and fingerprint collection is realized through the handheld terminal and the smart phone; for a light-colored background such as paper, a wall and the like, clear visible fingerprints are illuminated and collected by using a white light source module of the handheld terminal, the collected fingerprints are compared with fingerprint library information stored in the smart phone through a fingerprint feature extraction algorithm and a fingerprint feature comparison algorithm in the fingerprint analysis module, and meanwhile, the collected fingerprint images can be shared to other users through a wireless network to achieve cloud comparison.
A fingerprint extraction and identification method based on fluorescent materials comprises the following steps;
s1, fingerprint display: the fluorescent material magnetic fingerprint imaging powder is brushed and displayed on the fingerprint, and the redundant powder on the surface is absorbed, so that the fingerprint lines can be clearly displayed;
s2, fingerprint imaging and fingerprint extraction: covering a handheld terminal in a fingerprint acquisition area, enabling a macro lens to be positioned right above a fingerprint, switching an excitation light source module and controlling light intensity change through a light source control panel, operating a fingerprint extraction and analysis module in the smart phone, operating a fingerprint feature extraction algorithm, calling a smart phone camera to realize clear fingerprint imaging, performing image preprocessing and extracting fingerprint feature information;
s3, fingerprint identification: operating a fingerprint feature comparison algorithm, and comparing the fingerprint feature information extracted in the step S2 with fingerprint feature information which is extracted in advance through a fingerprint feature extraction algorithm or is directly imported into a fingerprint database to complete fingerprint identification;
s4, displaying the result: and the fingerprint extraction and analysis module displays the fingerprint identification result on the smart phone.
Compared with the prior art, the invention has the advantages that:
the invention develops a portable, single-person-operated and miniaturized portable fingerprint extraction and identification system and a method by combining the image acquisition and data processing functions of the smart phone with the photoelectric technology, and compared with the prior art, the system has the following advantages:
(1) the optical system is embedded into the handheld terminal and combined with the smart phone, so that the optical system is convenient to carry and can be realized without multi-person operation;
(2) different light sources can be provided under different environments, and processing is carried out by a self-adaptive local threshold method, so that the influence of different definitions under different environments on the identification effect is avoided;
(3) multiple technologies are integrated into a whole, so that the problems of different definitions from place to place and from person to person and the like can be avoided;
(4) combine fingerprint formation of image and fingerprint identification, the quick fingerprint authentication of realization is compared with high in the clouds in the built-in fingerprint storehouse of accessible, and the timeliness is high. The invention is suitable for rapid extraction and comparison of fingerprints in criminal sites, can be widely applied to other types of site trace analysis, such as palm prints, foot prints and the like, and has wide application and market prospects.
Drawings
Fig. 1 is a schematic axial view of a handheld terminal according to an embodiment of the present invention.
Fig. 2 is a top view of a handheld terminal in an embodiment of the invention.
Fig. 3 is a sectional view taken along a-a in fig. 2.
FIG. 4 is a functional flow diagram of the present invention.
FIG. 5 is a flowchart of a fingerprint extraction and identification method based on fluorescent material according to the present invention.
Detailed Description
In order to make the objects, technical solutions and features of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments; all other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
a fingerprint extraction and identification system based on fluorescent materials is shown in figure 4 and comprises a fingerprint library, a handheld terminal and a fingerprint extraction and analysis module;
in this embodiment, the handheld terminal includes a light source control board 5, an excitation light source module, a macro lens 6 and a smartphone camera;
a fingerprint feature extraction algorithm and a fingerprint feature comparison algorithm are built in the fingerprint analysis module;
the fingerprint analysis module runs a fingerprint feature extraction algorithm to call the handheld terminal to extract fingerprint feature information, and then runs a fingerprint feature comparison algorithm to compare the extracted fingerprint feature information with information in a fingerprint library of a cloud side, so that fingerprint identification is realized.
Before fingerprint extraction, fingerprint imaging magnetic powder made of fluorescent luminescent materials is brushed and displayed on a fingerprint, and redundant powder on the surface is absorbed, so that fingerprint lines are clearly displayed;
in this embodiment, the fingerprint extraction and analysis module and the smartphone camera are both implemented by the smartphone 1, wherein the fingerprint extraction and analysis module is mounted in an android environment to operate, and the smartphone camera is a camera in the smartphone 1 and is used for observing fingerprint imaging in cooperation with the macro lens 6 to extract fingerprint features;
the excitation light source module comprises a fluorescence excitation light source module 7 and a white light excitation light source module 8 and is used for realizing fingerprint imaging of the fingerprint powder to be printed under different fingerprint extraction conditions, and the fluorescence excitation light source module 7 is an ultraviolet light source and is used for providing excitation light with uniform irradiation light spots in a fingerprint acquisition area; the white light excitation light source module 8 is used for providing white light with uniform light intensity and illuminating light spots, and the fingerprints are directly imaged under a light-colored background.
In this embodiment, the fluorescence excitation light source module 7 includes an ultraviolet lamp 7-1, an ultraviolet light uniformizing lens 7-2 and an ultraviolet filter 7-3, and the white light source module 8 includes a white light lamp 8-1, a white light uniformizing lens 8-2 and a white light uniformizing sheet 8-3.
When the fingerprint feature extraction algorithm is operated, a camera of the smart phone is called to shoot, an excitation light source module is switched and light intensity change is controlled through a light source control panel 5 under different fingerprint extraction conditions to excite a fluorescent material, clear image amplification is completed through a macro lens 6 in the handheld terminal, clear fingerprint imaging is realized, a proper fingerprint acquisition area is selected, image preprocessing is performed, and fingerprint features are extracted;
the information in the fingerprint library is fingerprint feature information stored in the smartphone 1, which is extracted in advance through a fingerprint feature extraction algorithm or directly imported.
The image preprocessing is to remove the interference of uneven brightness and other noises in the fingerprint image by a series of processing on the original collected fingerprint image, and restore the line information of the real image by line thinning and repairing, and specifically comprises the following steps:
carrying out gray level processing on the acquired image, and carrying out image gray level normalization processing by adopting a self-adaptive local binarization image separation method; fingerprint image enhancement is carried out; carrying out image background segmentation to remove noise interference in the fingerprint as much as possible; searching a maximum gray value in the image as an initial value according to the sequence; calculating a direction value or ridge frequency to carry out local Gabor filtering; determining the next point of ridge line tracking; and comparing the data, judging whether the end condition is met or not according to a preset threshold, if so, returning to the starting point for direction tracking, and if the reverse tracking is finished, searching the maximum gray value again for other point analysis until the whole fingerprint image is traversed.
The image gray scale normalization processing is to perform image processing by adopting a local mean method in a self-adaptive local binarization method, divide a fingerprint image into image blocks which are not overlapped and have uniform sizes, and calculate the variance of each block according to the gray scale of the image blocks: the gray scale of the image block is obtained by calculating the mean value of the gray scale values in the image block; the gray value variance of the image block is obtained by calculating the mean value of the pixel gray value and the average gray value in the image block; setting a threshold value for the variance, comparing the variance with the threshold value, and separating the background from the fingerprint ridge area. The method is realized on the basis that the variance of a background area is small, and the variance of a fingerprint area is large due to ridge and valley structures, and if the variance of a certain image block is not zero or has a large threshold difference, threshold segmentation processing is further adopted for the area, specifically as follows:
the fingerprint image has a size of m × m, and is divided into image blocks of uniform size that do not overlap with each other, and the block size is n × n. In the fingerprint image, the abscissa and ordinate positions of an image block in the fingerprint image are indicated (i, j), and the coordinate positions of pixels in the image block are indicated (u, v);
the sum of the gray values of the points in the image block is calculated according to the following formula:
wherein L (u, v) is a pixel gray scale value in an image block, M (i, j) is a gray scale sum of an image block of the (i, j) th block, i is 1, 2 … k, j is 1, 2 … k, and k is M/n;
the gray variance of the image block is:
a (i, j) is the mean value of the gray values in the image blocks of the (i, j), and an effective fingerprint area and a background area can be judged by setting a threshold value of V (i, j);
selecting threshold value TdIf V (i, j)>TdIf the value of the corresponding image block in the image block (i, j) is set to F (i, j) ═ 1, then the area where the image block is located is an effective fingerprint area block; otherwise, the value of the image block is set to F (i, j) ═ 0, and the image block is a background region block.
The light source control panel 5 comprises a light source switch, a light intensity control function, a light source switching function and a charging function, can realize the switching of ultraviolet light sources and white light sources in different environments, is convenient for equipment in different environments to use, can realize the charging function, is convenient for the equipment to use at any time, and displays the normally bright power state lamp when the lamp is turned on.
As shown in fig. 1, in the present embodiment, the light source control board 5 includes a light source switch 5-1, a brightness increasing key 5-2, a brightness decreasing key 5-3, a power indicator 5-4, and a charging interface 5-5; and the light source switching can be realized by simultaneously pressing the brightness increasing key 5-2 and the brightness reducing key 5-3.
In this embodiment, as shown in fig. 2, the macro lens 6 and the smartphone camera are sequentially arranged right above the fingerprint acquisition area; the fluorescence excitation light source module 7 and the white light excitation light source module 8 are symmetrically distributed at the front and the back of the two sides of the macro lens 6, have the same height and are sequentially and closely arranged; the macro lens 6 and the optical axis of the smart phone camera form an included angle of 45% with the central optical axis of the fluorescence excitation light source module 7 and the central optical axis of the white light excitation light source module 8.
The fingerprint imaging collection can be carried out on the site fingerprint by using a white light source module 8 or a fluorescence excitation light source module 7 according to the requirement; under a complex background, the fluorescent material is excited through the fluorescent excitation light source module 7, so that fingerprint highlighting is realized, and fingerprint collection is realized through a handheld terminal; to under the light color background like paper, wall etc., clear visible fingerprint then uses handheld terminal's white light source module 8 to realize that the image illuminates and gathers, and the fingerprint that gathers obtained is compared with the fingerprint storehouse of saving in smart mobile phone 1 through fingerprint feature extraction algorithm and fingerprint feature comparison algorithm in the fingerprint analysis module, can also realize the high in the clouds and compare through sharing the fingerprint image of gathering to other users through wireless network simultaneously.
A fingerprint extraction and identification method based on fluorescent materials is shown in figure 5 and comprises the following steps;
s1, fingerprint display: the fluorescent material magnetic fingerprint imaging powder is brushed and displayed on the fingerprint, and the redundant powder on the surface is absorbed, so that the fingerprint lines can be clearly displayed;
s2, fingerprint imaging and fingerprint extraction: covering a handheld terminal in a fingerprint acquisition area, enabling a macro lens 6 to be positioned right above a fingerprint, switching an excitation light source module and controlling light intensity change through a light source control panel 5, operating a fingerprint extraction and analysis module in the smart phone 1, operating a fingerprint feature extraction algorithm, calling a smart phone camera to realize clear fingerprint imaging, performing image preprocessing, and extracting fingerprint feature information;
s3, fingerprint identification: operating a fingerprint feature comparison algorithm, and comparing the fingerprint feature information extracted in the step S2 with fingerprint feature information which is extracted in advance through a fingerprint feature extraction algorithm or is directly imported into a fingerprint database to complete fingerprint identification;
s4, displaying the result: the fingerprint extraction and analysis module displays the result of the fingerprint identification on the smartphone 1.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A fingerprint extraction and identification system based on fluorescent materials is characterized by comprising a fingerprint library, a handheld terminal and a fingerprint extraction and analysis module;
the handheld terminal comprises a light source control panel, an excitation light source module, a macro lens and a smart phone camera;
a fingerprint feature extraction algorithm and a fingerprint feature comparison algorithm are built in the fingerprint analysis module;
an operator places a fingerprint in a sampling area of the handheld terminal, the fingerprint analysis module operates a fingerprint feature extraction algorithm to call the handheld terminal to extract fingerprint feature information, and then operates a fingerprint feature comparison algorithm to compare the extracted fingerprint feature information with information in a fingerprint library, so that fingerprint identification is realized.
2. The fingerprint extraction and identification system based on fluorescent materials as claimed in claim 1, wherein the fingerprint imaging magnetic powder made of fluorescent luminescent materials is brushed and displayed on the fingerprint before fingerprint extraction, and the redundant powder on the surface is absorbed, so that the fingerprint lines can be clearly displayed;
the fingerprint extraction and analysis module and the fingerprint camera imaging are both realized through a smart phone, wherein the fingerprint extraction and analysis module is carried in an android environment to operate, and the camera is a camera in the smart phone and is matched with a macro lens to observe fingerprint imaging so as to extract fingerprint characteristics.
3. The fingerprint extraction and identification system based on fluorescent materials as claimed in claim 2, wherein the excitation light source module comprises a fluorescence excitation light source module and a white light excitation light source module, and is used for realizing fingerprint imaging of the fingerprint powder to be printed under different fingerprint extraction conditions, and the fluorescence excitation light source module is an ultraviolet light source and is used for providing excitation light with uniform irradiation light spots in a fingerprint collection area; the white light excitation light source module is used for providing white light with uniform light intensity and illuminating light spots, and the fingerprints are directly imaged under a light-colored background.
4. The fingerprint extraction and identification system based on the fluorescent material as claimed in claim 3, wherein when the fingerprint feature extraction algorithm is running, a smartphone camera is called to shoot, the light source control board switches the excitation light source module and controls the light intensity change under different fingerprint extraction conditions to excite the fluorescent material, the macro lens in the handheld terminal is used to complete the image clear amplification, so as to realize the clear imaging of the fingerprint, a proper fingerprint collection area is selected to perform image preprocessing, and the fingerprint feature is extracted;
the information in the fingerprint database is fingerprint characteristic information which is extracted in advance through a fingerprint characteristic extraction algorithm or is directly imported and stored in the smart phone.
5. The fingerprint extraction and identification system based on fluorescent materials as claimed in claim 4, wherein the image preprocessing is to remove the interference of brightness unevenness and other noises in the fingerprint image by a series of processing on the original collected fingerprint image, and restore the information of the lines of the real image by line thinning and repairing, specifically as follows:
carrying out gray level processing on the acquired image, and carrying out image gray level normalization processing by adopting a self-adaptive local binarization image separation method; fingerprint image enhancement is carried out; carrying out image background segmentation to remove noise interference in the fingerprint; searching a maximum gray value in the image as an initial value according to the sequence; calculating a direction value or ridge frequency to carry out local Gabor filtering; determining the next point of ridge line tracking; and comparing the data, judging whether the end condition is met or not according to a preset threshold, if so, returning to the starting point for direction tracking, and if the reverse tracking is finished, searching the maximum gray value again for other point analysis until the whole fingerprint image is traversed.
6. The fingerprint extraction and identification system based on fluorescent materials as claimed in claim 5, wherein the image gray scale normalization process is an image process by using a local mean method in an adaptive local binarization method, and by dividing the fingerprint image into non-overlapping image blocks with uniform size, the variance of each image block is calculated according to the gray scale of the image block: the gray scale of the image block is obtained by calculating the mean value of the gray scale values in the image block; the gray value variance of the image block is obtained by the mean value of the pixel gray value and the average gray value in the image block; setting a threshold value for the variance, comparing the variance with the threshold value, and separating the background from the fingerprint ridge area; if the variance of a certain image block is not zero or has a large difference with the threshold, further performing threshold segmentation processing on the area; the mean variance algorithm is specifically as follows:
the size of the fingerprint image is m multiplied by m, the fingerprint image is divided into image blocks which are not overlapped with each other and have uniform size, and the size of each block is n multiplied by n; in the fingerprint image, the abscissa and ordinate positions of an image block in the fingerprint image are indicated (i, j), and the coordinate positions of pixels in the image block are indicated (u, v);
the sum of the gray values of the points in the image block is calculated according to the following formula:
wherein L (u, v) is a pixel gray scale value in an image block, M (i, j) is a gray scale sum of an image block of the (i, j) th block, i is 1, 2 … k, j is 1, 2 … k, and k is M/n;
the gray variance of the image block is:
a (i, j) is the mean value of the gray values in the image blocks of the (i, j), and an effective fingerprint area and a background area can be judged by setting a threshold value of V (i, j);
selecting threshold value TdIf V (i, j)>TdIf the value of the corresponding image block in the image block (i, j) is set to F (i, j) ═ 1, then the area where the image block is located is an effective fingerprint area block; otherwise, the value of the image block is set to F (i, j) ═ 0, and the image block is a background region block.
7. The fingerprint extraction and identification system based on fluorescent materials of claim 4, wherein the light source control board comprises a light source switch, a light intensity control, a light source switching function and a charging function, can realize the switching of ultraviolet light sources and white light sources under different environments, is convenient for equipment under different environments to use, can realize the charging function through the built-in battery, is convenient for the equipment to use at any time, and is normally on when being turned on.
8. The fingerprint extraction and identification system based on fluorescent materials of claim 4, wherein the macro lens and the smart phone camera are sequentially arranged right above the fingerprint collection area; the fluorescence excitation light source module and the white light excitation light source module are symmetrically distributed at the front and the back of the two sides of the macro lens, have the same height and are sequentially and closely arranged; the macro lens and the optical axis of the smart phone camera form an included angle of 45 degrees with the central optical axes of the fluorescence excitation light source module and the white light excitation light source module.
9. The fingerprint extraction and identification system based on the fluorescent material as claimed in any one of claims 1 to 8, wherein a white light source module or a fluorescence excitation light source module can be used for fingerprint imaging collection as required for on-site fingerprints; under a complex background, the fluorescent material is excited through the fluorescence excitation light source module, fingerprint highlight is realized, and fingerprint collection is realized through the handheld terminal and the smart phone; under the light color background, the white light source module of the handheld terminal is used for realizing image illumination and collection of the clear visible fingerprints, the collected fingerprints are compared with fingerprint library information stored in the smart phone through a fingerprint feature extraction algorithm and a fingerprint feature comparison algorithm in the fingerprint analysis module, and meanwhile, the collected fingerprint images can be shared to other users through a wireless network to realize cloud comparison.
10. A fluorescent material-based fingerprint extraction and identification method of a fluorescent material-based fingerprint extraction and identification system according to claim 9, comprising the steps of;
s1, fingerprint display: the fluorescent material magnetic fingerprint imaging powder is brushed and displayed on the fingerprint, and the redundant powder on the surface is absorbed, so that the fingerprint lines can be clearly displayed;
s2, fingerprint imaging and fingerprint extraction: covering a handheld terminal in a fingerprint acquisition area, enabling a macro lens to be positioned right above a fingerprint, switching an excitation light source module and controlling light intensity change through a light source control panel, operating a fingerprint extraction and analysis module in the smart phone, operating a fingerprint feature extraction algorithm, calling a smart phone camera to realize clear fingerprint imaging, performing image preprocessing and extracting fingerprint feature information;
s3, fingerprint identification: operating a fingerprint feature comparison algorithm, and comparing the fingerprint feature information extracted in the step S2 with fingerprint feature information which is extracted in advance through a fingerprint feature extraction algorithm or is directly imported into a fingerprint database to complete fingerprint identification;
s4, displaying the result: and the fingerprint extraction and analysis module displays the fingerprint identification result on the smart phone.
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