CN115273249A - Spectrum three-dimensional identification method, spectrum three-dimensional identification method device and readable storage medium - Google Patents
Spectrum three-dimensional identification method, spectrum three-dimensional identification method device and readable storage medium Download PDFInfo
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- CN115273249A CN115273249A CN202210913849.2A CN202210913849A CN115273249A CN 115273249 A CN115273249 A CN 115273249A CN 202210913849 A CN202210913849 A CN 202210913849A CN 115273249 A CN115273249 A CN 115273249A
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- 238000001228 spectrum Methods 0.000 title claims abstract description 78
- 238000000034 method Methods 0.000 title claims abstract description 47
- 230000003595 spectral effect Effects 0.000 claims description 79
- 239000000463 material Substances 0.000 claims description 12
- 238000001514 detection method Methods 0.000 claims description 5
- 239000000126 substance Substances 0.000 abstract description 14
- 230000008569 process Effects 0.000 description 6
- 238000004891 communication Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- XUMBMVFBXHLACL-UHFFFAOYSA-N Melanin Chemical compound O=C1C(=O)C(C2=CNC3=C(C(C(=O)C4=C32)=O)C)=C2C4=CNC2=C1C XUMBMVFBXHLACL-UHFFFAOYSA-N 0.000 description 2
- 210000003128 head Anatomy 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- IISBACLAFKSPIT-UHFFFAOYSA-N bisphenol A Chemical compound C=1C=C(O)C=CC=1C(C)(C)C1=CC=C(O)C=C1 IISBACLAFKSPIT-UHFFFAOYSA-N 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000005284 excitation Effects 0.000 description 1
- 210000001061 forehead Anatomy 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000001727 in vivo Methods 0.000 description 1
- 238000002329 infrared spectrum Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 210000004279 orbit Anatomy 0.000 description 1
- 230000000149 penetrating effect Effects 0.000 description 1
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/40—Spoof detection, e.g. liveness detection
- G06V40/45—Detection of the body part being alive
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/64—Three-dimensional objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
Abstract
The invention discloses a spectrum three-dimensional identification method, an identification method device and a readable storage medium, which comprises the steps of obtaining three-dimensional information and spectrum information in a target area; traversing a pre-stored spectrum database and matching with the spectrum information; and if the acquired spectrum information is matched with a spectrum data in the spectrum database, outputting the pre-stored information corresponding to the matched spectrum data. The spectrum three-dimensional identification method provided by the invention can obtain the specific spectrum of the substance by using different spectrum filter pixels, assist in judging the substance characteristics of the object to be detected, and further improve the accuracy and reliability of biological identification.
Description
Technical Field
The invention relates to the field of spectrum identification, in particular to a spectrum three-dimensional identification method, an identification method device and a readable storage medium.
Background
At present, a human face as a kind of biological characteristic information is widely applied to the aspects of personal identity verification, video monitoring, human-computer interaction and the like, compared with other biological characteristic information such as iris, fingerprint and the like, the human face has the characteristics of non-contact and long-distance realization, and the current human face three-dimensional sensing technology is widely applied to consumer electronic products, wherein besides comparing human face three-dimensional information, a person with a heart is also prevented from imitating a human face mask of other people for passing verification.
Disclosure of Invention
The invention mainly aims to provide a spectral three-dimensional identification method, a spectral three-dimensional identification device and a readable storage medium, and aims to solve the problems.
In order to achieve the above object, the present invention provides a spectral three-dimensional identification method, comprising the following steps:
acquiring three-dimensional information and spectral information in a target area;
traversing a pre-stored spectrum database and matching with the spectrum information;
and if the acquired spectrum information is matched with a spectrum data in the spectrum database, outputting the pre-stored information corresponding to the matched spectrum data.
In an embodiment, after the step of matching the acquired spectral information with a spectral data in the spectral database, the spectral three-dimensional identification method further includes:
and if the pre-stored information is displayed as a human face, analyzing the three-dimensional information and delimiting a human face area.
In an embodiment, after the step of analyzing the three-dimensional information and defining the face region, the spectral three-dimensional recognition method further includes:
positioning key feature points of the human face to obtain position information of the key feature points of the human face;
and extracting the spectral data according to the position information of the key feature points of the human face in the human face area, performing living body detection, and judging whether the human face is a living body.
In an embodiment, the step of analyzing the three-dimensional information and delimiting the face region includes:
determining a curvature value and an orientation of the curvature of each vertex according to the three-dimensional information;
and dividing a face region and a background region based on the curvature value and the orientation.
In an embodiment, the curvature comprises at least one of a principal curvature, a gaussian curvature and an average curvature.
In an embodiment, after the step of acquiring the spectral information and matching the spectral data in the spectral database, the method for three-dimensional identification of spectra further includes:
if the pre-stored information is a non-human face, comparing the spectral characteristics with the spectral characteristics of pre-stored spectral data respectively to obtain a plurality of spectral comparison results corresponding to the spectral data respectively;
and according to the plurality of spectrum comparison structures, determining the closest spectrum comparison result in each spectrum data to obtain the surface material of the article.
In addition, in order to achieve the above object, the present invention further provides an identification device, which includes a memory, a processor, and a spectral three-dimensional identification program stored on the memory and operable on the processor, wherein the spectral three-dimensional identification program, when executed by the processor, implements the steps of the spectral three-dimensional identification method as described above.
Further, to achieve the above object, the present invention also provides a computer readable storage medium having stored thereon a spectral three-dimensional recognition program which, when executed by a processor, implements the steps of the spectral three-dimensional recognition method as described above.
The spectrum three-dimensional identification method, the identification device and the readable storage medium provided by the embodiment of the invention can acquire the three-dimensional information of the object to be detected, and can acquire the spectrum information of the object to be detected according to the pixels of different spectrums, and because different substances have different spectrums, the acquired spectrum information can be compared with the spectrum data in the spectrum database, so that the substance characteristics of the object to be detected can be identified. The invention can obtain the specific spectrum of the substance by using different spectrum filter pixels, assist in judging the substance characteristic of the object to be detected, and further improve the accuracy and reliability of biological identification.
Drawings
FIG. 1 is a schematic diagram of an apparatus in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flowchart of a three-dimensional spectral recognition method according to a first embodiment of the present invention;
fig. 3 is a composition diagram of a pixel.
The implementation, functional features and advantages of the present invention will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the terminal may include: a processor 1001, e.g. a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. The processor 1001 may connect various parts of the entire identification device using various interfaces and lines, and perform various functions of the identification device and process data by operating or executing software programs and/or modules stored in the memory 1005 and calling data stored in the memory 1005, thereby performing overall monitoring of the identification device. A communication bus 1002 is used to enable connection communications between these components. The user interface 1003 may include a Display (Display), an input unit such as a Keyboard (Keyboard), keys, a touch panel, and the like, and the optional user interface 1003 may also include a standard wired interface, a wireless interface, and the like. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory such as a disk memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the terminal may further include a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WiFi module, and the like. Of course, the hardware device may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, and so on, which are not described herein again.
Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a spectral three-dimensional recognition program.
In the terminal shown in fig. 1, the processor 1001 may be configured to call the spectral three-dimensional identification program stored in the memory 1005 and perform the following operations:
acquiring three-dimensional information and spectral information in a target area;
traversing a prestored spectrum database and matching with the spectrum information;
and if the acquired spectrum information is matched with a spectrum data in the spectrum database, outputting the pre-stored information corresponding to the matched spectrum data.
Further, the processor 1001 may call the spectral three-dimensional identification program stored in the memory 1005, and further perform the following operations:
and if the pre-stored information is displayed as a face, analyzing the three-dimensional information and demarcating a face area.
Further, the processor 1001 may call the spectral three-dimensional identification program stored in the memory 1005, and further perform the following operations:
positioning key feature points of the human face to obtain position information of the key feature points of the human face;
and extracting the spectral data according to the position information of the key feature points of the human face in the human face area, performing living body detection, and judging whether the human face is a living body.
Further, the processor 1001 may call the spectral three-dimensional identification program stored in the memory 1005, and further perform the following operations:
determining the curvature value and the orientation of the curvature of each vertex according to the three-dimensional information;
and dividing a face region and a background region based on the curvature value and the orientation.
Further, the processor 1001 may call the spectral three-dimensional identification program stored in the memory 1005, and further perform the following operations:
if the pre-stored information is a non-human face, comparing the spectral characteristics with the spectral characteristics of pre-stored spectral data respectively to obtain a plurality of spectral comparison results corresponding to the spectral data respectively;
and according to the plurality of spectrum comparison structures, determining the closest spectrum comparison result in each spectrum data to obtain the surface material of the article.
The specific embodiment of the application identification device of the present invention is basically the same as the following embodiments of the application spectrum three-dimensional identification method, and is not described herein again.
Referring to fig. 2, fig. 2 is a schematic flow chart of a spectral three-dimensional identification method according to a first embodiment of the present invention, wherein the spectral three-dimensional identification method includes the following steps:
step S10, acquiring three-dimensional information and spectral information in a target area;
each pixel is composed of a plurality of sub-pixels (F1-F16) with different penetrating spectra and SPAD pixels, and the SPAD can obtain a histogram and obtain object distances; sub-pixels (F1-F16) having different transmission spectra mean that the characteristic spectrum of said substance DIAN can be obtained, since different substances have different characteristic spectra, it is possible to distinguish the nature of the substance according to the information obtained on the spectrum.
Step S20, traversing a pre-stored spectrum database and matching with the spectrum information;
step S30, if the acquired spectrum information is matched with a spectrum data in the spectrum database
In this embodiment, the three-dimensional information of the object to be measured is obtained, and the spectral information of the object to be measured can be obtained according to the pixels of different spectra, and since different substances have different spectra, the obtained spectral information can be compared with the spectral data in the spectral database, so as to identify the substance characteristics of the object to be measured. The invention can obtain the specific spectrum of the substance by using different spectrum filter pixels, assist in judging the substance characteristic of the object to be detected, and further improve the accuracy and reliability of biological identification.
And if the pre-stored information is displayed as a human face, analyzing the three-dimensional information and demarcating a human face area.
Specifically, referring to fig. 3, after the step of analyzing the three-dimensional information and defining a face region, the spectral three-dimensional identification method further includes:
positioning key feature points of the human face to obtain position information of the key feature points of the human face;
and extracting the spectral data according to the position information of the key feature points of the human face in the human face area, performing living body detection, and judging whether the human face is a living body.
In this embodiment, a hyperspectral camera is used to obtain a hyperspectral image of a target area, where the hyperspectral image includes a plurality of hyperspectral images of different wave bands. Preferably, the spectral images of different wave bands comprise a 550nm wave band hyperspectral image, a 685nm wave band hyperspectral image and a 850nm wave band hyperspectral image; due to the influence of special substances such as skin melanin, the skin reflection curve has the W characteristic in the 550nm wave band, namely the skin reflection curve of real skin near the wave band forms a W shape, so that the skin recognition is promoted, materials simulating human skin diffraction can be distinguished, and more real modeling and rendering of human skin are facilitated; the kit is suitable for in vivo detection in 850nm wave band; for the 685nm band, different races can be distinguished. It is to be understood that the above bands are merely exemplary, and the embodiments of the present invention are not limited to the above bands.
Specifically, the step of analyzing the three-dimensional information and defining a face region includes:
determining the curvature value and the orientation of the curvature of each vertex according to the three-dimensional information;
and dividing a face area and a background area based on the curvature value and the orientation.
The curvature includes at least one of a principal curvature, a gaussian curvature, and an average curvature.
In one embodiment, the gaussian curvature uniquely determines the shape of the convex surface, while the mean curvature uniquely determines the shape of the graphical surface under certain complementary conditions. By analyzing the signs of the gaussian curvature and the average curvature, the geometric features in the neighborhood of a certain point on the curved surface can be obtained to detect the human face. Specifically, when the gaussian curvature is positive, zero, or negative, the local curved surfaces correspond to an ellipsoid, a parabola, and a hyperboloid, respectively.
The sign of the average curvature indicates the concave-convex characteristic of the neighborhood curved surface, and when the average curvature is non-negative, the neighborhood curved surface is a convex surface; otherwise, when the average curvature is negative, the neighborhood curved surface is a concave surface. It should be understood that there may be many different combinations according to the sign of gaussian curvature and the sign of mean curvature, which correspond to curved surfaces with different characteristics, respectively, and can preliminarily classify the vertexes of the three-dimensional surface, thereby dividing the face from the background.
In one embodiment, the face and background are partitioned by computing the eigenvalues (curvature values of the principal curvatures) and eigenvectors (principal curvature orientations) of the shape operators. The curvature map contains the principal curvature of each pixel, i.e. the eigenvalue with the larger absolute value and the corresponding curvature orientation. The original curvature may be positive or negative, wherein a positive curvature corresponds to a convex surface pattern and a negative curvature corresponds to a concave surface pattern, and a body part such as a head is convex in nature and has a strong positive curvature.
Furthermore, pixels with positive curvature values have a light gray shade in the curvature map, while pixels with negative curvature values are dark gray, the transition from positive to negative curvature being a good indication of the edge of the face part, so that the face and the background can be clearly divided. It should be understood that the definition of positive and negative curvature is arbitrary and can be defined as negative curvature as a convex surface pattern, which is not limited herein.
Although the shape of the curved surface of the face area is relatively complicated due to eyes, nose, mouth and eye sockets, the curve of the face area runs from the forehead to the top of the head, runs from the cheek to two sides and runs from the chin to the neck, and the common characteristic point of the three directions is that the curved surface has a process of changing from relatively flat to relatively curved. Thus, the variation can be scaled by gaussian curvature, mean curvature and shape operators.
In another embodiment, the spectral three-dimensional identification method provided by the invention can identify not only a human body, but also an article.
Specifically, after the step of matching the acquired spectrum information with a spectrum data in the spectrum database, the spectrum three-dimensional identification method further includes:
if the pre-stored information is a non-human face, comparing the spectral characteristics with the spectral characteristics of pre-stored spectral data respectively to obtain a plurality of spectral comparison results corresponding to the spectral data respectively;
and according to the plurality of spectrum comparison structures, determining the closest spectrum comparison result in each spectrum data to obtain the surface material of the article.
Because the component element of different materials is different, different element through the excitation of specific light high energy, different characteristic light can be launched in the interact between the atom, through the spectral feature of analysis characteristic light, judges the composition of material, confirms the material of waiting to discern article surface. At present, infrared spectrum recognition is commonly used for spectrum recognition, infrared light is emitted to the surface of an article to be recognized, characteristic light is emitted from the surface of the article to be recognized after the surface of the article to be recognized is irradiated by the infrared light, and the spectral characteristics of the characteristic light are compared with the spectral characteristics corresponding to all materials included in a spectrum database to determine the material of the surface of the article to be recognized.
In addition, the invention also provides a computer readable storage medium, on which the spectrum three-dimensional identification program is stored. The computer-readable storage medium may be the Memory 20 in the terminal in fig. 1, and may also be at least one of a ROM (Read-Only Memory)/RAM (Random Access Memory), a magnetic disk, and an optical disk, where the computer-readable storage medium includes several instructions to enable a terminal device (which may be an identification apparatus, a smart television, a mobile phone, a computer, a server, or a network device) with a processor to execute the spectral three-dimensional identification method according to various embodiments of the present invention.
It is to be understood that throughout the description of the present specification, references to "an embodiment", "another embodiment", "other embodiments", or "first through nth embodiments", etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes performed by the present invention or directly or indirectly applied to other related technical fields are also included in the scope of the present invention.
Claims (8)
1. A spectral three-dimensional identification method is characterized by comprising the following steps:
acquiring three-dimensional information and spectral information in a target area;
traversing a pre-stored spectrum database and matching with the spectrum information;
and if the acquired spectrum information is matched with a spectrum data in the spectrum database, outputting the pre-stored information corresponding to the matched spectrum data.
2. The method according to claim 1, wherein after the step of matching the acquired spectral information with a spectral data in the spectral database, the method further comprises:
and if the pre-stored information is displayed as a human face, analyzing the three-dimensional information and delimiting a human face area.
3. The spectral three-dimensional recognition method according to claim 2, wherein after the step of analyzing the three-dimensional information and defining a human face region, the spectral three-dimensional recognition method further comprises:
positioning key feature points of the human face to obtain position information of the key feature points of the human face;
and extracting the spectral data according to the position information of the key feature points of the human face in the human face area, performing living body detection, and judging whether the human face is a living body.
4. The spectral three-dimensional recognition method of claim 2, wherein the step of analyzing the three-dimensional information and delimiting the human face region comprises:
determining a curvature value and an orientation of the curvature of each vertex according to the three-dimensional information;
and dividing a face area and a background area based on the curvature value and the orientation.
5. The spectral three-dimensional identification method according to claim 4, wherein said curvature comprises at least one of a principal curvature, a Gaussian curvature, and an average curvature.
6. The method according to claim 2, wherein after the step of matching the acquired spectral information with a spectral data in the spectral database, the method further comprises:
if the pre-stored information is a non-human face, comparing the spectral characteristics with the spectral characteristics of pre-stored spectral data respectively to obtain a plurality of spectral comparison results corresponding to the spectral data respectively;
and according to the plurality of spectrum comparison structures, determining the closest spectrum comparison result in each spectrum data to obtain the surface material of the article.
7. A spectral three-dimensional recognition apparatus, comprising a memory, a processor, and a spectral three-dimensional recognition program stored on the memory and executable on the processor, wherein: the spectroscopic three-dimensional identification program when executed by the processor implements the steps of the spectroscopic three-dimensional identification method of any one of claims 1 to 8.
8. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a spectral three-dimensional identification program, which when executed by a processor implements the steps of the spectral three-dimensional identification method according to any one of claims 1 to 8.
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| CN104568749A (en) * | 2013-10-25 | 2015-04-29 | 中国移动通信集团公司 | Objective surface material identification method, device and identification equipment and system |
| CN111611977A (en) * | 2020-06-05 | 2020-09-01 | 吉林求是光谱数据科技有限公司 | Face recognition monitoring system and recognition method based on spectrum and multiband fusion |
| CN112232109A (en) * | 2020-08-31 | 2021-01-15 | 深圳奥比中光科技有限公司 | Living body face detection method and system |
| US20220222464A1 (en) * | 2021-01-13 | 2022-07-14 | Ford Global Technologies, Llc | Material spectroscopy |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104568749A (en) * | 2013-10-25 | 2015-04-29 | 中国移动通信集团公司 | Objective surface material identification method, device and identification equipment and system |
| CN111611977A (en) * | 2020-06-05 | 2020-09-01 | 吉林求是光谱数据科技有限公司 | Face recognition monitoring system and recognition method based on spectrum and multiband fusion |
| CN112232109A (en) * | 2020-08-31 | 2021-01-15 | 深圳奥比中光科技有限公司 | Living body face detection method and system |
| US20220222464A1 (en) * | 2021-01-13 | 2022-07-14 | Ford Global Technologies, Llc | Material spectroscopy |
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Address after: Room 50A, 5th Floor, Block C, Building 24, Science and Technology Innovation Park, Gangwan 1, Jintang Road, Tangjiawan Town, High tech Zone, Zhuhai City, Guangdong Province, 519000 Applicant after: Sibote Integrated Technology (Zhuhai) Co.,Ltd. Applicant after: Yifutong Integrated Technology (Zhuhai Hengqin) Co.,Ltd. Address before: Room 509, Building 18, Hengqin Creative Valley, No. 1889 Huandao East Road, Hengqin New District, Zhuhai City, Guangdong Province, 519000 Applicant before: Smart Integrated Technology (Zhuhai Hengqin) Co.,Ltd. Applicant before: Yifutong Integrated Technology (Zhuhai Hengqin) Co.,Ltd. |
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| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230629 Address after: Room 2104, Office Building, No. 191 Rongzhu Road, Hengqin New District, Zhuhai City, Guangdong Province, 519000 Applicant after: Yifutong Integrated Technology (Zhuhai Hengqin) Co.,Ltd. Address before: Room 50A, 5th Floor, Block C, Building 24, Science and Technology Innovation Park, Gangwan 1, Jintang Road, Tangjiawan Town, High tech Zone, Zhuhai City, Guangdong Province, 519000 Applicant before: Sibote Integrated Technology (Zhuhai) Co.,Ltd. Applicant before: Yifutong Integrated Technology (Zhuhai Hengqin) Co.,Ltd. |