CN109977891A - A kind of object detection and recognition method neural network based - Google Patents
A kind of object detection and recognition method neural network based Download PDFInfo
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- CN109977891A CN109977891A CN201910254154.6A CN201910254154A CN109977891A CN 109977891 A CN109977891 A CN 109977891A CN 201910254154 A CN201910254154 A CN 201910254154A CN 109977891 A CN109977891 A CN 109977891A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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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
Abstract
The invention discloses a kind of object detection and recognition methods neural network based comprising the steps of: A, uses the image information in image acquisition device detection zone；B, identifying processing is carried out to acquired image, neural network model C, is established by computer；D, the main modular of convolutional neural networks is defined；E, collected image information is detected using neural network model calculating, and completes numerical result output；F, it makes mark on the image according to testing result, position and the classification of the mark in each target is marked with rectangle frame；The result of judgement detection and identification；G, the result of identification and detection is verified；The present invention is based on the object detection and recognition methods of neural network to carry out recognition of face using object detection and recognition, and arithmetic speed is fast, and judging result is accurate, effectively increases the precision of detection and the efficiency of identification.
Description
Technical field
The present invention relates to a kind of nerual network technique field, specifically a kind of object detection and recognition neural network based
Method.
Background technique
Nowadays, with the fast development of the correlation theory of computer vision and application study, computer vision technique exists
The superiority applied in daily life also increasingly highlights.Carrying out identification to image with computer is computer from relevant view
Corresponding feature is extracted in frequency or image sequence, to allow the content of computer " understanding " image, and the skill that can correctly classify
Art.The promotion of security protection consciousness also allows people constantly soaring for public and personal demand for security, so that computer nerve net
Network technology in terms of have very high application value.
Target detection is an important research topic in computer vision field.It has been widely used in multiple
In the application of real scene, such as recognition of face, traffic safety, population surveillance and image retrieval.Real-time mesh based on deep learning
Mark detection refers to position and the classification that target object is marked in a secondary natural scene picture or video.In face of magnanimity
Image/video data, handmarking is time-consuming, inefficient, automation and quick object detection method be there is an urgent need to.
Influence due to object detection and recognition effect vulnerable to many factors, and requirement of the neural network for data does not have
It is so harsh, and discrimination is higher.So convolutional neural networks have important theory for the research of field of face identification
Meaning and realistic meaning.
Summary of the invention
The purpose of the present invention is to provide a kind of object detection and recognition methods neural network based, to solve the back
The problem of being proposed in scape technology.
In order to achieve the object, the invention provides the following technical scheme:
A kind of object detection and recognition method neural network based comprising the steps of:
A, using the image information in image acquisition device detection zone；
B, identifying processing is carried out to acquired image,
C, neural network model is established by computer；
D, the main modular of convolutional neural networks is defined；
E, collected image information is detected using neural network model calculating, and completes numerical result output；
F, it makes mark on the image according to testing result, position and the classification of the mark in each target is marked with rectangle frame；
The result of judgement detection and identification；
G, the result of identification and detection is verified.
As further technical solution of the present invention: the step A is realized by camera.
As further technical solution of the present invention: the step B is specifically: by the image in collected certain time
Global alignment is carried out, if the comparison results are consistent, then the picture still being judged as in this time, occur without dynamic object,
Be automatically deleted this section of time acquired image information, therefore, it is determined that this section of temporal image is invalid image, when comparison result not
Unanimously, then the image zooming-out for difference occur is come out, determines the image of this time for images to be recognized.
As further technical solution of the present invention: the step E is specifically to format the label information of every image
And be written in a txt file, while also extracting picture point different from raw frames in the image, scheme as difference
Picture.
As further technical solution of the present invention: further including step F: carrying out algorithm simulating, and be improved identification
Algorithm is built experiment porch and is verified, wherein algorithm simulating passes through MATLAB software realization.
Compared with prior art, the beneficial effects of the present invention are: the present invention is based on the object detection and recognitions of neural network
Method carries out recognition of face using object detection and recognition, and arithmetic speed is fast, and judging result is accurate, effectively increases detection
The efficiency of precision and identification.
Specific embodiment
The technical scheme in the embodiments of the invention will be clearly and completely described below, it is clear that described implementation
Example is only a part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, this field is common
Technical staff's every other embodiment obtained without making creative work belongs to the model that the present invention protects
It encloses.
A kind of embodiment 1: object detection and recognition method neural network based comprising the steps of:
A, using the image information in image acquisition device detection zone；
B, identifying processing is carried out to acquired image, the image in collected certain time is subjected to global alignment, if
Comparison result is consistent, then the picture still being judged as in this time, occurs without dynamic object, and being automatically deleted this time adopts
The image information collected when comparison result is inconsistent, then difference will occur therefore, it is determined that this section of temporal image is invalid image
Image zooming-out comes out, and determines the image of this time for images to be recognized.
C, neural network model is established by computer；
D, the main modular of convolutional neural networks is defined；
E, collected image information is detected using neural network model calculating, and completes numerical result output；It will be every
The label information for opening image is formatted and is written in a txt file, while also by figure different from raw frames in the image
Picture point extracts, as difference image；
F, it makes mark on the image according to testing result, position and the classification of the mark in each target is marked with rectangle frame；
The result of judgement detection and identification；
G, the result of identification and detection is verified.
H, algorithm simulating is carried out, and builds experiment porch for improved recognizer and is verified, wherein algorithm simulating
Pass through MATLAB software realization.
Wherein, step A is realized by camera.The equipment such as mobile phone, digital camera can also be first used to realize.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case where without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, no matter
From the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by appended power
Benefit requires rather than above description limits, it is intended that all by what is fallen within the meaning and scope of the equivalent elements of the claims
Variation is included within the present invention.
In addition, it should be understood that although this specification is described in terms of embodiments, but not each embodiment is only wrapped
Containing an independent technical solution, this description of the specification is merely for the sake of clarity, and those skilled in the art should
It considers the specification as a whole, the technical solutions in the various embodiments may also be suitably combined, forms those skilled in the art
The other embodiments being understood that.
Claims (5)
1. a kind of object detection and recognition method neural network based, which is characterized in that comprise the steps of:
Use the image information in image acquisition device detection zone；
Identifying processing is carried out to acquired image,
Neural network model is established by computer；
Define the main modular of convolutional neural networks；
Collected image information is detected using neural network model calculating, and completes numerical result output；
It makes mark on the image according to testing result, position and the classification of the mark in each target is marked with rectangle frame；Sentence
The result of disconnected detection and identification；
The result of identification and detection is verified.
2. a kind of object detection and recognition method neural network based according to claim 1, which is characterized in that described
Step A is realized by camera.
3. a kind of object detection and recognition method neural network based according to claim 2, which is characterized in that described
Step B is specifically: the image in collected certain time being carried out global alignment, if the comparison results are consistent, then is judged as
Picture still in this time occurs without dynamic object, is automatically deleted this section of time acquired image information, therefore sentence
Fixed this section of temporal image is invalid image, when comparison result is inconsistent, then comes out the image zooming-out for difference occur, determines the section
The image of time is images to be recognized.
4. a kind of object detection and recognition method neural network based according to claim 3, which is characterized in that described
Step E be specifically the label information of every image is formatted and is written in a txt file, while also by the image with original
The different picture point of beginning picture extracts, as difference image.
5. a kind of object detection and recognition method neural network based according to claim 4, which is characterized in that also wrap
It includes step H: carrying out algorithm simulating, and build experiment porch for improved recognizer and verified, wherein algorithm simulating is logical
Cross MATLAB software realization.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111076659A (en) * | 2019-12-02 | 2020-04-28 | 深圳市太赫兹科技创新研究院有限公司 | Signal processing method, device, terminal and computer readable storage medium |
| CN112364844A (en) * | 2021-01-12 | 2021-02-12 | 北京三维天地科技股份有限公司 | Data acquisition method and system based on computer vision technology |
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