CN109214328A - Face grasping system based on face recognition engine - Google Patents
Face grasping system based on face recognition engine Download PDFInfo
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- CN109214328A CN109214328A CN201810995718.7A CN201810995718A CN109214328A CN 109214328 A CN109214328 A CN 109214328A CN 201810995718 A CN201810995718 A CN 201810995718A CN 109214328 A CN109214328 A CN 109214328A
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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
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/166—Detection; Localisation; Normalisation using acquisition arrangements
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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
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Abstract
Face grasping system disclosed by the invention based on face recognition engine, it is related to technical field of image processing, including face detection module, facial calibration module and face recognition module, wherein, face detection module uses the MB-LBP characteristics algorithm based on OpenCV, the frame image sent for real-time reception camera, face detection module is also used to, whether judgment frame image includes facial image, if, then save frame image, facial calibration module, for being positioned to the facial image in frame image, it generates Face detection image and positioning image is sent to face recognition module, face recognition module, for receiving the Face detection image of facial calibration module transmission and extracting facial characteristics from Face detection image, generate crawl image, improve the efficiency of face grasping system, precision, grab the face of fearness It is low and grab the low defect of the pixel of the facial image of fearness to solve low efficiency existing for existing face grasping system, precision for the pixel of image.
Description
Technical field
The present invention relates to technical field of image processing, and in particular to a kind of face crawl system based on face recognition engine
System.
Background technique
In recent years, flourishing with artificial intelligence technology, face recognition technology have obtained wide in industry and life
General application.During application face recognition technology, it will usually be realized using the camera of intelligent mobile terminal to face figure
The crawl of picture.Common camera (price is medium or relatively low) is usually not embedded in good face grasping algorithm, only has biography
The mobile detection screenshot of system crosses the functions such as line crawl, may grab when carrying out facial image crawl not comprising face
Image.And for the camera with Face datection function, the ability for intercepting facial image is not strong, realizes that facial image is cut
The time interval taken is longer, and the face pixel being truncated to is lower, more fuzzy.
Summary of the invention
To solve the deficiencies in the prior art, the face crawl based on face recognition engine that the embodiment of the invention provides a kind of
System, the system include: face detection module, facial calibration module and face recognition module, in which:
The face detection module uses multiple dimensioned piece of local binary patterns (the Multiscale Block based on OpenCV
Local Binary Pattern, MB-LBP) characteristics algorithm, the frame image sent for real-time reception camera；
The face detection module is also used to, and judges whether the frame image includes facial image, if so, described in saving
Frame image；
The facial calibration module generates Face detection figure for positioning to the facial image in the frame image
The positioning image is simultaneously sent to the face recognition module by picture；
The face recognition module, for receiving Face detection image that the facial calibration module is sent and from the people
Facial characteristics is extracted in face positioning image, generates crawl image.
Preferably, the MB-LBP characteristics algorithm uses 4 × 4 neighborhood window algorithms.
Face grasping system provided in an embodiment of the present invention based on face recognition engine has following
The utility model has the advantages that
The pixel for the facial image that can efficiently, accurately realize the crawl to facial image and grab is higher.
Detailed description of the invention
Fig. 1 is that the composed structure of the face grasping system provided in an embodiment of the present invention based on face recognition engine is illustrated
Figure；
Fig. 2 is 3 × 3 neighborhood window schematic diagrames in MB-LBP characteristics algorithm.
Specific embodiment
Specific introduce is made to the present invention below in conjunction with the drawings and specific embodiments.
As shown in Figure 1, the face grasping system provided in an embodiment of the present invention based on face recognition engine includes:
Face detection module, facial calibration module and face recognition module, wherein
The face detection module uses the MB-LBP characteristics algorithm based on OpenCV, sends for real-time reception camera
Frame image.
Wherein, the thought of MB-LBP characteristics algorithm is to extract window feature using structuring thought, and statisticsization is recycled to do
The extraction of final global feature.
As shown in Fig. 2, by taking the MB-LBP characteristics algorithm using 3 × 3 neighborhood windows as an example, the MB-LBP characteristics algorithm step
It is as follows:
(1) 8- neighborhood territory pixel value is compared with central point pixel value, it is adjacent above or equal to the 8- of central point pixel
Domain pixel value is labeled as 1, is otherwise labeled as 0；
(2) 0-1 sequence is sequentially arranged, at one 8 signless binary numbers and by the binary system
Number is converted to integer, which is the MB-LBP value for characterizing 3 × 3 neighborhood window.
Further, by taking Fig. 2 as an example, which is (10101001)2=169.
The face detection module is also used to, and judges whether the frame image includes facial image, if so, described in saving
Frame image.
The facial calibration module generates Face detection figure for positioning to the facial image in the frame image
The positioning image is simultaneously sent to the face recognition module by picture.
The face recognition module, for receiving Face detection image that the facial calibration module is sent and from the people
Facial characteristics is extracted in face positioning image, generates crawl image.
Optionally, the MB-LBP characteristics algorithm uses 4 × 4 neighborhood window algorithms.
Face grasping system provided in an embodiment of the present invention based on face recognition engine, including face detection module, face
Portion's calibration module and face recognition module, wherein face detection module uses the MB-LBP characteristics algorithm based on OpenCV, is used for
The frame image that real-time reception camera is sent, face detection module are also used to, and whether judgment frame image includes facial image, if
It is then to save frame image, facial calibration module generates Face detection figure for positioning to the facial image in frame image
As and by positioning image is sent to face recognition module, face recognition module, for receiving the face of facial calibration module transmission
Positioning image simultaneously extracts facial characteristics from Face detection image, generates crawl image, improve face grasping system efficiency,
Precision, grab fearness facial image pixel.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, there is no the portion being described in detail in some embodiment
Point, reference can be made to the related descriptions of other embodiments.
It is understood that the correlated characteristic in the above method and device can be referred to mutually.In addition, in above-described embodiment
" first ", " second " etc. be and not represent the superiority and inferiority of each embodiment for distinguishing each embodiment.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
Algorithm and display are not inherently related to any particular computer, virtual system, or other device provided herein.
Various general-purpose systems can also be used together with teachings based herein.As described above, it constructs required by this kind of system
Structure be obvious.In addition, the present invention is also not directed to any particular programming language.It should be understood that can use various
Programming language realizes summary of the invention described herein, and the description done above to language-specific is to disclose this hair
Bright preferred forms.
In addition, memory may include the non-volatile memory in computer-readable medium, random access memory
(RAM) and/or the forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM), memory includes extremely
A few storage chip.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, calculating equipment includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/
Or the forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable Jie
The example of matter.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
It include so that the process, method, commodity or the equipment that include a series of elements not only include those elements, but also to wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including element
There is also other identical elements in process, method, commodity or equipment.
It will be understood by those skilled in the art that embodiments herein can provide as method, system or computer program product.
Therefore, complete hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects can be used in the application
Form.It is deposited moreover, the application can be used to can be used in the computer that one or more wherein includes computer usable program code
The shape for the computer program product implemented on storage media (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Formula.
The above is only embodiments herein, are not intended to limit this application.To those skilled in the art,
Various changes and changes are possible in this application.It is all within the spirit and principles of the present application made by any modification, equivalent replacement,
Improve etc., it should be included within the scope of the claims of this application.
It should be noted that the above embodiments do not limit the invention in any form, it is all to use equivalent replacement or equivalent change
The mode changed technical solution obtained, falls within the scope of protection of the present invention.
Claims (2)
1. a kind of face grasping system based on face recognition engine, including face detection module, facial calibration module and face
Identification module, which is characterized in that
The face detection module uses the multiple dimensioned piece of local binary patterns MB-LBP characteristics algorithm based on OpenCV, for real
When receive camera send frame image；
The face detection module is also used to, and judges whether the frame image includes facial image, if so, saving the frame figure
Picture；
The facial calibration module generates Face detection image simultaneously for positioning to the facial image in the frame image
The positioning image is sent to the face recognition module；
The face recognition module, for receiving the Face detection image of the facial calibration module transmission and determining from the face
Facial characteristics is extracted in bit image, generates crawl image.
2. system according to claim 1, which is characterized in that the MB-LBP characteristics algorithm is calculated using 4 × 4 neighborhood windows
Method.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112150552A (en) * | 2020-09-30 | 2020-12-29 | 南京鹰视人工智能科技有限公司 | Spatial positioning method based on face recognition and point cloud fusion of surveillance video |
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