TW202203088A - Infrared recognition method for human body - Google Patents

Abstract

The present invention provides an infrared recognition method for human body. The infrared recognition method includes an irradiation step, an acquisition step, an image analysis step, a select step, and a recognition step. The irradiation step is implemented by irradiating to a target to generate a plurality of laser tiles from each other. The acquisition step is implemented by capturing a basic image for the target. The image analysis step is implemented by comparing the basic image and analyzed to generate an identification image. The identification image has multiple reflectance information corresponding to the laser tiles. The select step is implemented by dividing the identification image into multiple recognition areas, and a part of the recognition areas corresponding to the target is selected and defined as a detection area. Calculate an average reflectance for the multiple reflectance information in each detection area. The recognition step is implemented by identifying by a classifier according to the average reflectance in each of the detection areas to confirm whether it is a human body.

Description

Infrared human body recognition method

The invention relates to a human body identification method, in particular to an infrared human body identification method for identifying whether a target is a human body through infrared laser light.

The existing human body recognition method uses an infrared camera (also known as an IR camera) to photograph a human body twice to obtain an ambient light image (NIR) without near-infrared light and an infrared light image with near-infrared light ( NIRL), and then identify the position of the human face in the ambient light image and the infrared light image through a face detector, and then identify the human face in the infrared light image corresponding to the human face The image information of the part position replaces the image information corresponding to the position of the human face in the ambient light image, so as to generate a near-infrared differential image (NIRD) used as an identification image, and through a The classifier analyzes and identifies the features (reflectivity) in the near-infrared light differential image to confirm whether the human body is a real human being.

However, in this method, two shots are required to obtain the ambient light image and the infrared light image, and then the near-infrared light differential image can be obtained for identification. Displaced significantly to avoid the position difference of the human body in the ambient light image and the infrared light image being too large, causing the face detector to be unable to identify the position of the human body, or causing the human body to shake. The near-infrared light differential image has an afterimage, so that the classifier cannot confirm the features in the infrared light differential image, and cannot analyze and identify.

Therefore, the inventor believes that the above-mentioned defects can be improved. Nate has devoted himself to research and application of scientific principles, and finally proposes an invention with reasonable design and effective improvement of the above-mentioned defects.

The technical problem to be solved by the present invention is to provide an infrared human body identification method in view of the deficiencies of the prior art, which can effectively improve the possible defects of the existing human body identification method.

The embodiment of the present invention discloses an infrared human body identification method, which includes: performing an irradiation step: irradiating a target with an infrared laser light, so that the outer surface of the target forms a plurality of laser blocks arranged at intervals from each other, and the An ambient light area irradiated by an ambient light is formed on the outer surface of the target between any two of the laser blocks; a capturing step is performed: an image information capturing device is used to capture the target at the target. A basic image is captured on the outer surface, the basic image has a plurality of first image information corresponding to a plurality of the laser blocks and a plurality of second image information corresponding to the plurality of the ambient light areas respectively ; Implementing an image simulation step: in the base image, the second image information corresponding to any two adjacent ambient light areas is obtained by an interpolation method to obtain a simulation information, and the simulation information replaces the corresponding two The first image information of the laser blocks between the ambient light areas to generate a simulated image simulating that the target is only illuminated by the ambient light; implementing an image analysis step: converting the The basic image and the simulated image are compared and analyzed to remove the image information of the ambient light, and an identification image is generated, and the identification image has a plurality of reflections on the target corresponding to the plurality of laser blocks implementing a recognition step: identifying the identified image through a classifier; wherein, the classifier identifies through a plurality of the reflectance information in the identified image to confirm whether the target is a a human body.

The embodiment of the present invention further discloses an infrared human body identification method, which includes: performing an irradiation step: irradiating a target with an infrared laser light, so that the outer surface of the target forms a plurality of laser blocks arranged at intervals from each other, and An ambient light area irradiated by an ambient light is formed on the outer surface of the target between any two of the laser blocks; a capturing step is performed: an image information capturing device is used to capture the target at the target. A base image is captured on the outer surface of the base image, the base image has a plurality of first image information corresponding to a plurality of the laser blocks and a plurality of second images respectively corresponding to the plurality of the ambient light areas information; implementing an image analysis step: analyzing a plurality of the first image information and a plurality of the second image information in the basic image to generate an identification image, the identification image has a plurality of the lasers A plurality of reflectance information of the image block on the target; implementing an identification step: identifying the identification image through a classifier; wherein, the classifier uses a plurality of the reflectances in the identification image. The information is identified to confirm whether the target is a human body.

To sum up, in the infrared human body recognition method disclosed in the embodiment of the present invention, a plurality of the laser image blocks spaced apart from each other are generated on the target by the infrared laser light, which can be used in the capturing step. Acquire the basic image with the infrared laser light image information; accordingly, by directly analyzing the first image information in the basic image (that is, the image information corresponding to a plurality of the laser blocks), And the high-precision identification image is acquired.

Furthermore, the infrared human body recognition method disclosed in the embodiment of the present invention can further divide the recognition image into a plurality of the recognition areas, and select a plurality of the detection areas (some of the detection areas) corresponding to the target. According to this, the classifier can identify the image features in each of the detection areas, so as to avoid the situation that the identification cannot be analyzed.

For a further understanding of the features and technical content of the present invention, please refer to the following detailed descriptions and drawings of the present invention. However, the drawings provided are only for reference and description, and are not intended to limit the present invention.

The following is a description of the implementation of the "infrared human body recognition method" disclosed in the present invention through specific specific examples, and those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the concept of the present invention. In addition, the drawings of the present invention are merely schematic illustrations, and are not drawn according to the actual size, and are stated in advance. The following embodiments will further describe the related technical contents of the present invention in detail, but the disclosed contents are not intended to limit the protection scope of the present invention.

It should be understood that although terms such as "first", "second" and "third" may be used herein to describe various elements or signals, these elements or signals should not be limited by these terms. These terms are primarily used to distinguish one element from another element, or a signal from another signal. In addition, the term "or", as used herein, should include any one or a combination of more of the associated listed items, as the case may be.

[First Embodiment]

As shown in FIG. 1 to FIG. 8 , which are the first embodiment of the present invention, this embodiment discloses an infrared human body recognition method, and the above infrared human body recognition method is to obtain ambient light and Image information of infrared light for human body recognition. In other words, a method for acquiring image information with ambient light and infrared light through more than one capture, or a method for performing human body identification without using infrared light and ambient light, is not the human body identification method referred to in this embodiment.

The infrared human body identification method includes: an irradiation step S110, a capture step S120, an image simulation step S140, an image analysis step S150, a selection step S160, and an identification step S170. It should be noted that, any one of the above-mentioned steps can be omitted or replaced by a reasonable change according to the needs of the designer.

Carrying out the irradiation step S110 : irradiating a target G with an infrared laser light L, so that the outer surface of the target G forms a plurality of laser blocks LG arranged at intervals, and the outer surface of the target G forms a plurality of laser blocks LG An ambient light area EA illuminated by an ambient light E is formed between any two of the laser blocks LG. It should be noted that the outer surface of the target G is exposed to the ambient light E, that is, when the infrared laser light L is irradiated on the outer surface of the target G, each The location of the laser block LG also has the ambient light E instead of the infrared laser light L alone.

Specifically, a plurality of the laser image blocks LG generated by the infrared laser light L are presented on the outer surface of the target G in the form of longitudinal stripes, and a plurality of the laser images The total number of blocks LG is not less than 6, and the ambient light area EA is formed between any two of the laser blocks LG, and the ambient light area EA is not affected by the infrared laser light L. The irradiated area is not limited to that set forth in this example. For example, in other embodiments of the present invention that are not shown, the plurality of the laser blocks LG can be adjusted according to the needs of the designer, for example, the plurality of the laser blocks LG can also be in the horizontal direction. The means are located on the outer surface of the target G, and the number is 20.

Further, the wavelength of the infrared laser light L needs to be not less than 800 nanometers (nm), and the reflectivity of the infrared laser light L on the skin surface (outer surface) of the human body is greater than that of the infrared laser light L. More than 5% of the non-skin surface (for example: silicone); and in this embodiment, the wavelength of the infrared laser light L is 840-860 nm, and the infrared laser light L irradiates the skin surface of the human body The reflectivity of the infrared laser light L is greater than 15% of the reflectivity of the non-skin surface irradiated by the infrared laser light L, but is not limited to what is described in this embodiment.

In other words, as shown in the graph in FIG. 2 , this graph is used to show that the infrared laser light L of different wavelengths irradiates the light-colored silica gel surface, the dark-colored silica gel surface, the light-colored skin surface, and the dark-colored skin surface. Reflectance, the horizontal axis of this graph is wavelength (nm), and the vertical axis is reflectance (%). The surface is made of silicone or other similar materials to form fake faces of different skin tones. From this chart, it can be clearly found that when the wavelength of the infrared laser light L is 840-860 nm, the reflectance irradiated on the dark and light-colored skin surfaces is significantly different from that on the dark and light-colored silicone surfaces.

Carry out the capturing step S120 : as shown in FIG. 3 , capture a base image P1 on the outer surface of the target G by an image information capturing device C, and the base image P1 has corresponding multiple A plurality of first image information P11 of each of the laser blocks LG and a plurality of second image information P12 corresponding to a plurality of the ambient light areas EA respectively. Specifically, the outer surface of the target G is exposed to the ambient light E, that is, the first image information P11 corresponding to each of the laser blocks LG includes the The image information of the infrared laser light L and the ambient light E, and each of the first image information P11 has only the image information of the ambient light E. It should be noted that, in this embodiment, the image information capturing device C can emit the infrared laser light L (as shown in FIG. 1 and FIG. 9 ).

Carrying out the image simulation step S140 : as shown in FIG. 4 , in the base image P1 , the second image information P12 corresponding to any two adjacent ambient light areas EA is obtained by an interpolation method. Simulation information A, the simulation information A replaces the first image information P11 corresponding to the laser block LG between the two ambient light areas EA, so as to generate a simulation of the target G only affected by the environment A simulated image P2 illuminated by light E; in other words, the simulated image P2 removes each of the first image information P11 in the base image P1, and then removes any two adjacent first image information P11. The analog information A is calculated by interpolation (the interpolation method) from the two image information P12, and the analog information A replaces the first image information P11 that has been removed between the two second image information P12.

Perform the image analysis step S150 : referring to FIG. 5 , compare and analyze the basic image P1 and the simulated image P2 to remove the image information of the ambient light E (that is, a plurality of the second images The information P12 and a plurality of the simulation information A) are used to generate an identification image P3, and the identification image P3 has a plurality of reflectance information corresponding to the plurality of the laser blocks LG on the target; in detail , the identification image P3 is obtained by subtracting the image information of the ambient light E in the basic image P1 from the image information of the ambient light E in the simulated image P2, so that the identification image P3 does not have any The image information of the ambient light E only has the reflectivity of the plurality of the laser blocks LG (the plurality of the first image information P11 ) on the outer surface of the target G.

The selection step S160 is implemented: as shown in FIG. 6 , the identification image P3 is divided into a plurality of identification areas P31 , and each of the identification areas P31 has a plurality of the reflectivity information; In the area P31, a part of the identification area P31 corresponding to the target G is selected, and is respectively defined as a detection area Y, and a plurality of the reflectivity information in each of the detection areas Y is calculated to obtain a Average reflectance.

Specifically, the identification image P3 defines a first direction D1 and a second direction D2 that are perpendicular to each other, and a plurality of the identification regions P31 are arranged in M rows parallel to the first direction D1 and parallel to the first direction D1. In the N columns of the two directions D2, M and N are positive integers greater than 2; that is, the plurality of identification regions P31 are arranged in an M-by-N matrix (checkerboard shape). As shown in FIG. 6 , in this embodiment, a plurality of the identification regions P31 are arranged in 5 rows parallel to the first direction D1 and 4 columns parallel to the second direction D2, that is, a plurality of the The number of identification areas P31 is 20, and a plurality of the detection areas Y are a plurality of the identification areas P31 except for the eyes corresponding to the target G; in detail, as shown in FIG. 6 , A plurality of the identification areas P31 are sequentially defined as a first identification area, a second identification area, a third identification area, . . . , and a twentieth identification area from top to bottom and left to right, and many In this embodiment, the detection areas Y are the second identification area, the third identification area, the fourth identification area, the twelfth identification area, the thirteenth identification area, the fourteenth identification area, and the tenth identification area. The seventh identification area, the eighteenth identification area, and the nineteenth identification area, that is to say, the plurality of detection areas Y are outside the second column from top to bottom in FIG. 6 and correspond to the target G. The identification regions P31 are not limited to those in this embodiment.

Further, a plurality of the identification regions P31 in the middle 1/3 position of the identification image P3 corresponding to the target G from top to bottom (that is, the first direction D1 ) are respectively defined as a different In the detection area N, the plurality of the detection areas Y are not located in the plurality of the non-detection areas N. In detail, referring to FIG. 7 , a plurality of the non-detection regions N are located in the second column from the top to the bottom of the identification image P3 , but are not limited to those described in this embodiment. For example, in other embodiments not shown in the present invention, the identification images P3 are divided into 48 and arranged in 6 rows parallel to the first direction D1 and 8 rows parallel to the second direction D2 Columns (that is, arranged in a 6-by-8 matrix), the plurality of identification regions P31 located in the third and fourth columns from top to bottom are defined as a plurality of the non-detection regions N. In other words, the multiple non-detection areas N correspond to the eye positions of the target G (human body); accordingly, it is possible to avoid capturing the reflectivity information of the target G (human body) wearing glasses.

Carrying out the identifying step S170 : identifying the identifying image P3 through a classifier (not shown in the figure); wherein, the classifier identifies through the mean value of the reflectivity in each of the detection areas Y , to determine whether the target G is a human body. Specifically, the classifier is a Support Vector Machine (SVM) in this embodiment, and the classifier is identified by the mean value of the reflectivity in each of the detection areas Y, so as to It is confirmed whether some of the mean values of reflectivity are larger than the other mean values of reflectivity to make a determination.

In order to enable those skilled in the art to better understand the process of the present invention in the identification step S170, an example will be given below, and the target in this example is a fake face made of silicone (not shown in the figure). shown), the fake face simulates the real facial features, and the irradiation step S110, the capture step S120, the position confirmation step S130, the image simulation step S140, and the image analysis step have been performed in sequence. S150, and the selection step S160; that is, the fake face will implement the identification step S170.

When the skin surface is directly irradiated by the image information capture device C, except for the part corresponding to the forehead of the human body, the skin surface is a smooth surface, and other parts of the skin surface cannot face the image information capture directly. The device C has an angle, so that the infrared laser light L is not easily received when it is irradiated on the other parts of the skin surface, resulting in a low reflectivity of the other parts of the skin surface, and is close to The reflectivity of the fake face, therefore, when the infrared laser light L illuminates the skin surface, the infrared laser light L will have a strong reflectivity at the forehead position corresponding to the skin surface, and The reflectivity of the other positions on the skin surface is lower, that is to say, the detection areas Y of the forehead corresponding to the skin surface have a higher mean reflectance value, while the corresponding A plurality of the detection areas Y at the other positions on the skin surface have a lower mean value of the reflectivity; on the contrary, the reflectivity of the fake face is very similar whether it is the forehead or other parts.

In other words, as shown in the graph in FIG. 8 , this graph is the reflectance when the infrared laser light L is irradiated on the fake face and the skin surface at different angles; wherein, the horizontal axis is the angle of incidence, and the vertical axis The axis is reflectance. From the graph, it can be clearly seen that when the infrared laser light L irradiates the skin surface at different incident angles, the corresponding reflectivity is significantly different, and the infrared laser light L illuminates the fake face at different incident angles. When , the corresponding reflectance is relatively small compared to the former (that is, the reflectance irradiated on the skin surface).

That is to say, when the infrared laser light L irradiates the fake face and the human body with an incident angle close to 0 degrees, the reflectivity of the skin surface will be significantly greater than that of the fake face, especially if the The position of the forehead is the most obvious; on the contrary, when the infrared laser light L irradiates the fake face and the human body with an incident angle close to 90 degrees, the reflectivity of the skin surface will obviously approach that of the fake face. Reflectivity. Accordingly, through the difference in the reflectivity of the infrared laser light L on the surface of the silicone rubber and the surface of the skin, the classifier can identify the fake face as a non-real human body through the difference in the mean values of the reflectivity.

In addition, it should be noted that the plurality of the detection areas Y are not located in the non-detection area N is to avoid the high reflectivity average value of the mirror surface of the glasses being captured when the human body wears glasses, which may cause the classifier to make a misjudgment Case.

It can be clearly seen from the above description that the infrared human body recognition method only needs to pass the irradiation step S110, the capture step S120, the image analysis step S150, the selection step S160, and the identification step S170. An accurate human body recognition effect can be achieved, and the infrared human body recognition method generally implements the image simulation step S140, which can further greatly improve the human body recognition accuracy.

[Second Embodiment]

This embodiment is similar to the above-mentioned first embodiment, and the similarities between the two embodiments will not be repeated, and the difference between this embodiment and the above-mentioned first embodiment mainly lies in that: in the implementation of the capturing step S120 and the Before performing the image simulation step S140, the infrared human body recognition method further includes performing a position confirmation step S130.

The position confirmation step S130 is performed: analyzing the base image P1 to confirm the positions of the plurality of first image information P11 in the base image P1. Specifically, the base image P1 includes red, blue, and green light information (RGB), and has a red channel (Channel R), a blue channel (Channel B), and a green channel (Channel G), The positions of a plurality of the first image information P11 in the basic image P1 are confirmed by the difference in reflection of the infrared laser light L by the red channel and the green channel, but not limited to this embodiment contained. For example, the base image P1 may also be based on the difference in reflection of the infrared laser light L by the red channel and the blue channel, so as to confirm the plurality of first image information P11 in the base image position in P1. Of course, the method of confirming the positions of the plurality of first image information P11 in the base image P1 may also be to obtain the plurality of first image information through the characteristic shape or high-frequency position of the base image P1 The position of P11 in the base image P1.

[Third Embodiment]

As shown in FIG. 9 , it is a third embodiment of the present invention. This embodiment is similar to the above-mentioned second embodiment, and the similarities between the two embodiments will not be repeated. Compared with the above-mentioned second embodiment, this embodiment The difference between the embodiments is mainly that: in the implementation of the irradiation step S110, the plurality of the laser image blocks LG are in a square shape, and the number of the plurality of the laser image blocks LG is greater than 50, so that the laser image blocks LG are located in any two The ambient light area EA is formed between the laser blocks LG. However, it should be noted that the number and shape of the plurality of laser blocks LG can be adjusted according to the needs of the designer. For example, the plurality of laser blocks LG can also be triangular, diamond, or irregular shapes, etc.

[Technical effects of the embodiments of the present invention]

To sum up, in the infrared human body recognition method disclosed in the embodiment of the present invention, the infrared laser light L generates a plurality of the laser blocks LG spaced apart from each other on the target G, so that the In the capturing step S110, the basic image P1 having the image information of the infrared laser light L is acquired; accordingly, by directly analyzing the first image information P11 in the basic image P1 (that is, corresponding to a plurality of The image information of the laser block LG) is obtained to obtain the high-quality identification image P3; in addition, the infrared human body identification method disclosed in the embodiment of the present invention can further divide the identification image P3 into multiple The identification areas P31 are selected, and a plurality of detection areas Y (part of the identification areas P31 ) corresponding to the target G are selected, so that the classifier can detect each detection area. The image features in the area Y are identified to avoid the situation where the identification cannot be analyzed.

The content disclosed above is only a preferred feasible embodiment of the present invention, and is not intended to limit the scope of the present invention. Therefore, any equivalent technical changes made by using the contents of the description and drawings of the present invention are included in the application of the present invention. within the scope of the patent.

G: target L: Infrared laser light LG: Laser Tiles E: ambient light EA: Ambient Light Area P1: Base Image P11: First Image Information P12: Second image information P2: Simulated image A: Simulation information P3: Identifying images P31: Identification area D1: first direction D2: Second direction Y: Detection area N: No detection area C: Image information capture device

FIG. 1 is a schematic diagram of the state of the infrared human body recognition method in the implementation of the irradiation step according to the first embodiment of the present invention.

FIG. 2 is a reference chart of the reflectivity of the infrared body recognition method of the first embodiment of the present invention when the infrared laser light irradiates the silicone surface and the skin surface with different wavelength bands.

3 is a schematic plan view of a basic image of the infrared human body recognition method according to the first embodiment of the present invention.

4 is a schematic plan view of a simulated image of the infrared human body recognition method according to the first embodiment of the present invention.

FIG. 5 is a schematic plan view of a recognized image of the infrared human body recognition method according to the first embodiment of the present invention.

6 is a schematic plan view of the infrared human body recognition method according to the first embodiment of the present invention when a plurality of recognition images are divided into a plurality of recognition areas.

7 is a schematic plan view of a non-detection area in a plurality of identification images of the infrared human body identification method according to the first embodiment of the present invention.

FIG. 8 is a reference chart of the reflectivity of each wavelength band of the infrared laser light irradiated on the silicone surface and the skin surface according to the infrared human body identification method according to the first embodiment of the present invention.

FIG. 9 is a schematic diagram of the state of the infrared human body recognition method in the implementation of the irradiation step according to the third embodiment of the present invention.

G: target

L: Infrared laser light

LG: Laser Tiles

E: ambient light

EA: Ambient Light Area

C: Image information capture device

Claims (10)

An infrared human body identification method, comprising: Implementing an irradiation step: irradiating an outer surface of a target with an infrared laser light, so that a plurality of laser blocks are formed on the outer surface of the target; A capturing step is implemented: capturing a base image on the outer surface of the target by an image information capturing device, the base image having a plurality of first image information corresponding to a plurality of the laser blocks respectively ; An image analysis step is implemented: the basic image is compared and analyzed by a plurality of the first image information to generate an identification image, and the identification image has a plurality of images corresponding to the plurality of the laser blocks on the target. reflectivity information; Implementing a selecting step: dividing the identification image into a plurality of identification areas, each of the identification areas having a plurality of the reflectivity information; in the plurality of the identification areas, selecting a portion corresponding to the target. The identification areas are respectively defined as a detection area, and a plurality of reflectivity average values are calculated from a plurality of the reflectivity information in each of the detection areas; Implementing an identification step: identifying a plurality of the detection areas through a classifier; wherein, the classifier identifies the average value of the reflectivity in each of the detection areas to identify a plurality of the detection areas Among the mean values of reflectivity, whether some of the mean values of reflectivity are greater than other mean values of reflectivity is used to determine whether the target is a human body. The infrared human body recognition method according to claim 1, wherein, in the selecting step, the recognition image defines a first direction and a second direction that are perpendicular to each other, and a plurality of the recognition areas are arranged in parallel to each other. For M rows in the first direction and N columns parallel to the second direction, M and N are each a positive integer greater than 2. The infrared human body identification method according to claim 2, wherein, in the selecting step, the identification areas in the second row from top to bottom of the identification image are respectively defined as a non-detection area , a plurality of the detection areas are not located in a plurality of the non-detection areas. The infrared human body recognition method according to claim 3, wherein the classifier is a Support Vector Machine (SVM); in the recognition image, a plurality of the recognition areas are arranged in parallel with the first 5 rows of directions and 4 columns parallel to the second direction. The infrared human body recognition method according to claim 1, wherein, in the selecting step, the recognition images are respectively corresponding to a plurality of the recognition regions at the middle 1/3 position from top to bottom of the target. Defined as a non-detection area, a plurality of the detection areas are not located in the non-detection areas. The infrared human body identification method according to claim 1, wherein the wavelength of the infrared laser light is not less than 800 nanometers (nm), and the reflectivity of the infrared laser light on the skin surface irradiating the human body is greater than the The reflectivity of the object irradiated by infrared laser light is more than 5%. The infrared human body recognition method according to claim 1, wherein, in the irradiating step, the outer surface of the target is formed with an ambient light irradiated between any two of the laser blocks. an ambient light area; in the capturing step, the base image has a plurality of second image information corresponding to a plurality of the ambient light areas respectively; between the capturing step and the image analyzing step , the infrared human body recognition method includes: implementing an image simulation step: in the basic image, the second image information corresponding to any two adjacent ambient light areas is obtained by an interpolation method to obtain a simulation information, the simulated information replaces the first image information corresponding to the laser block between the two ambient light regions to generate a simulated image simulating that the target is only illuminated by the ambient light; In the image analysis step, the basic image and the simulated image are compared and analyzed to remove the image information of the ambient light to generate the identification image, and the identification image has a corresponding plurality of the lasers A plurality of the reflectivity information of the tile on the target. An infrared human body identification method, comprising: Implementing an irradiation step: irradiating an outer surface of a target with an infrared laser light, so that a plurality of laser blocks are formed on the outer surface of the target; A capturing step is implemented: capturing a base image on the outer surface of the target by an image information capturing device, the base image having a plurality of first image information corresponding to a plurality of the laser blocks respectively ; An image analysis step is implemented: the basic image is compared and analyzed by a plurality of the first image information to generate an identification image, and the identification image has a plurality of images corresponding to the plurality of the laser blocks on the target. reflectivity information; Implementing a selecting step: dividing the identification image into a plurality of identification areas, each of the identification areas having a plurality of the reflectivity information; in the plurality of the identification areas, selecting a portion corresponding to the target. The identification areas are respectively defined as a detection area, and a plurality of reflectivity average values are calculated from a plurality of the reflectivity information in each of the detection areas; Implementing an identification step: identifying the identified image through a classifier; wherein, the classifier identifies through the mean value of the reflectivity in each of the detection areas to determine whether the target is a human body . The infrared human body recognition method according to claim 8, wherein, in the selecting step, the recognition images are respectively in a plurality of the recognition areas corresponding to the middle 1/3 position of the target from top to bottom. Defined as a non-detection area, a plurality of the detection areas are not located in the non-detection areas. The infrared human body recognition method according to claim 8, wherein, in the selecting step, the recognition image defines a first direction and a second direction that are perpendicular to each other, and a plurality of the recognition areas are arranged in parallel to each other. For M rows in the first direction and N columns parallel to the second direction, M and N are each a positive integer greater than 2.

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