NZ734556B2 - Image recognition system and method - Google Patents
Image recognition system and method Download PDFInfo
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- NZ734556B2 NZ734556B2 NZ734556A NZ73455615A NZ734556B2 NZ 734556 B2 NZ734556 B2 NZ 734556B2 NZ 734556 A NZ734556 A NZ 734556A NZ 73455615 A NZ73455615 A NZ 73455615A NZ 734556 B2 NZ734556 B2 NZ 734556B2
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- 238000001514 detection method Methods 0.000 claims abstract description 15
- 238000007781 pre-processing Methods 0.000 claims abstract description 10
- 238000000034 method Methods 0.000 claims description 9
- 230000000052 comparative effect Effects 0.000 claims description 6
- 230000000875 corresponding Effects 0.000 claims description 3
- 230000003068 static Effects 0.000 claims description 3
- 230000001502 supplementation Effects 0.000 claims 1
- 230000000007 visual effect Effects 0.000 description 3
- 210000000887 Face Anatomy 0.000 description 2
- 210000000554 Iris Anatomy 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000006011 modification reaction Methods 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 206010024855 Loss of consciousness Diseases 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000009432 framing Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
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- G06K9/00255—
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- G06K9/00268—
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- G06K9/00288—
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- G06K9/6269—
Abstract
The invention discloses an image recognition system, comprising: a robot having an image collection module configured to drive an image collection module to collect an image in a view of the robot by the image collection drive module; a light source configured to fill the light when the image collection module collecting an image; a face detection module configured to locate a face image in an image according to the image collected by the image collection module; a face recognition module configured to implement a preprocessing for the located face image, then the preprocessed face image being compared with an image feature information of a known identity in a database, to determine an identity information and a confidence rate of the present face image. The invention can identify a face based on a fixed face pose, and it can identify a face based on a local or web server database. tion module collecting an image; a face detection module configured to locate a face image in an image according to the image collected by the image collection module; a face recognition module configured to implement a preprocessing for the located face image, then the preprocessed face image being compared with an image feature information of a known identity in a database, to determine an identity information and a confidence rate of the present face image. The invention can identify a face based on a fixed face pose, and it can identify a face based on a local or web server database.
Description
IMAGE RECOGNITION SYSTEM AND METHOD
BACKGROUND OF THE INVENTION
1.Field of the Invention
The present disclosure relates to a security field, more
specifically, to a system and a method for image recognition for a robot
system.
2.Description of the Related Art
Nowadays, with the increasing requirements for the security, a
great number of security systems utilize password authentication for the
identification. Notwithstanding, this kind of identification lacks in
security, and people is easy to obtain the decryption method, thus the
high‐level security requirement is not satisfied. Therefore, the
authentication mode through the identification of the fingerprint, iris
and face is gradually adopted by the high‐level security system. The
human biological characteristics, such as face, fingerprint and iris, are
innate, the uniqueness and the difficulty of being duplicated are
necessary conditions for the identity authentication. The face
recognition has peculiar features compared with other types of
biological recognition, these feature are as follows:
non‐obligatory: the user does not need to fit the face collection
device, and the face collection device can obtain the face image when
the user is unconscious, thus the collection method has no “mandatory”;
non‐contact: the image is collected although the user does not
need to directly contact the device;
concurrency: the sorting, the determination and the
identification of a plurality of faces can be executed in the application
scenarios;
visual characteristic: people are identified by their faces, and the
operation is simple, the result is intuitional, the stealthiness is good.
At present, the face recognition system generally comprises a
camera configured to collect the face image, a light source configured to
fill light, an assistant position system or a sign configured to prompt the
face collection location, a computer (such as an embedded computer)
configured to execute the face recognition software, a device configured
to process or display the identification result such as a reminder light, a
relay configured to open the door, and a database sheet in order to
record the identification results.
The face recognition system for the security system has the
following issues in the application scenarios: 1. the requirement for the
pose of the face collection is fixed; 2. the light condition is sensitive and
should be fixed by filling the light; 3. it does not need high speed
calculating cause the calculating demand is one‐off.
SUMMARY OF THE INVENTION
To resolve the shortcoming of the prior art, the invention
provides an image recognition system, comprises:
a robot having an image collection module, configured to drive
the image collection module to collect an image in a view of the robot by
the image collection drive module;
a light source configured to fill the light when the image
collection module collecting an image;
a face detection module configured to locate a face image in the
image collected by the image collection module;
a face recognition module configured to implement a
preprocessing for the located face image, then the preprocessed face
image being compared with an image feature information of a known
identity contained in a database, to determine an identity information
and a confidence rate of the present face image.
Preferably, the image collection module is a high definition
camera, the high definition camera is capable to obtain static image and
to collect at least 30 images per second;
the high definition camera is connected to the robot by a MIPI or
a USB interface.
Preferably, the light source comprises an ambient light source
and an infrared light source;
upon utilizing the ambient light to fill the light and collecting the
image by the image collection module, if the collected image can not be
recognized, the light is filled by the infrared light source.
Preferably, the preprocessing comprising:
executing an angle correction treatment and a light treatment
(such as brightness normalization and polarized light correction) for the
face image presenting in the image.
Preferably, the database comprises a local data memory module
and a web server data memory module.
Preferably, the robot further comprises a sounding device
connected to the database, the sounding device sends out various types
of prompt tones according to a comparative result from the face
recognition module.
Preferably, the image recognition system further comprises a
record feedback device to record and/or feed back a comparative result
from the face recognition module.
Preferably, the face recognition module implements a
comparison by SVM algorithm.
A image recognition method for the above‐mentioned system,
comprises the steps of:
(a) collecting the image in the view of the robot by the image
collection module of the robot while filling the light by a light source as
the image collection module collecting the image;
(b) using the face detection module to implement a location
process to the face image presenting in the image which is collected by
the image collection module;
(c) using the face detection module to implement a
preprocessing for the face after being located, then comparing with an
image feature information of a known identity contained in a database,
to determine an identity information and a confidence rate of the
present face image.
Preferably, in the above method, if the identity information of
present face image is incompatible with an image feature information of
a known identity in a database, execute the step (a) to step (c)
continually.
BRIEF DESCRIPTIONS OF THE DRAWINGS
Referring to the accompanying drawings, the description made
by the unlimited embodiments, the disclosure and the feature, outline
and advantage thereof will be more obvious. The same signs in all
drawings indicate the same portions and they are not drawn in
proportion intentionally. It illustrates the meaning of the invention.
Figure 1 shows the identity recognition system structure and
the operation case thereof according to the present invention.
DETAILED DESCRIPTIONS
The following description provides the details to permit a better
comprehension of the invention. However, it is obvious for the people
skilled in the art that the invention can be implemented without any one
or more details. In other examples, to avoid confusion, the known
technical features in the art are not described.
To understand the invention thoroughly, the following
descriptions will provide detail steps and structures to explain the
technical solution for the invention. The preferred embodiment is
described as follows. However, the invention has further embodiments
beyond the detailed description.
Since the invention consists in a part of the robot visual system
to implement the face identification, the issues in the application of the
robot should be addressed. The issues comprise: 1 various poses of the
face presenting in a view of the robot; 2. various light condition,
including polarized light or no filling light source; 3. real‐time recognizing
the face in the view of the robot that demanding a quick response, and
the real‐time feedback implemented through a continuous recognition
in accordance with the variation of the identified face.
To resolve the above issues, the embodiment provides an image
recognition system, comprising:
a robot having an image collection module, configured to drive
the image collection module to collect an image in a view of the robot by
the image collection drive module;
a light source configured to fill the light when the image
collection module collecting an image;
a face detection module configured to locate a face image in the
image collected by the image collection module;
a face recognition module configured to implement a
preprocessing for the located face image, then the preprocessed face
image being compared with an image feature information of a known
identity contained in a database, to determine an identity information
and a confidence rate of the present face image.
In an embodiment of the invention, it is optional but unlimited
that, the image collection module of the robot is a high definition
camera. Preferably, the high definition camera is capable to obtain
static image and to collect at least 30 images per second, tofurther meet
the requirement of high‐speed image collection. For example, even if
the object in the view of the robot moves fast, the invention is also able
to collect the image clearly. It is optional but unlimited that, the high
definition camera is connected to the robot by a MIPI or an USB
interface. In some optional embodiments, the robot can implement a
real‐time adjustment for the framing scope or angle of the image
collection module througha motor. For example, if the image collection
module detects people crossing within the visual scope of it, the image
collection module can implement real‐time tracking snapshot by the
motor, such as moving with the object simultaneously and implementing
the enlarged amplifying snapshot immediately, to improve the definition
of the collected image.
In an embodiment of the invention, it is optional but unlimited
that, the above light source includes an ambient light source and an
infrared light source. The ambient light source is a build‐in light source
of the robot. The advantage of the ambient light source is homogeneity
of the lighting. However the disadvantage of the ambient light source is
that the luminance is low and it can not be directed. Furthermore, the
luminance can be controlled by other high‐level application, the light
even be closed sometimes. Hence, the ambient light can not meet the
requirement of filling light. Because a set of infrared light‐emitting
device is added to the invention and is used to fill the light of the image,
the lumination power is controlled by the image recognition system
limitedly, to achieve stable filling light in various scenarios. For example,
when the ambient light source is used to fill light and to collect image by
the image collection module, if the collected image can not meet the
requirement of the recognition, then the invention uses the infrared
light source to fill the light, thus to obtain a clear image.
In an embodiment of the invention, it is optional but unlimited
that, the face detection module implements the location, that is, the
face position is located in the full‐field image collected by the robot. In
the present security system, this step is unnecessary as the position is
fixed. Then preprocess the located face image by the face recognition
module, the preprocessed face image is compared with an image
feature information of a known identity in a database, to determine an
identity information and a confidence rate of the present face image.
The face recognition module can execute the angle correction treatment
and the light treatment (such as brightness normalization and polarized
light correction) for the face image presented in the image. Due to the
great change of the ambient and angle of the face collection, the
invention increases the recognition rate through the execution of the
angle correction treatment for the face image collected and located by
the face detection module. Meanwhile, the embedded recognition
technology also can process the light of the image, to facilitate the
comparison and to increase the accuracy.
In an embodiment of the invention, it is optional but unlimited
that, the above database includes a local data memory module and a
web server data memory module. Based on the embedded system of
the robot, the local data memory module adopts the face recognition
technology according to the feature matching. Firstly, the local data
memory module makes the feature database of the face image of a
known identity, secondly it extracts a same type of feature according to
the face image of the real‐time collection, comparing the feature
distance of the present face to the feature distance of the database face
through a math distance function. Finally, it determines the possible
identity, and gives out the confidence rate. Since the web server data
memory module has more computing resources and more flexible
application architectures, it adopts the face recognition technology
based on a deep learning model which is configured to generate the face
feature in the database, to construct the face category in the database
by SVM (Support Vector Machine) algorithm or other standard
classifiers. Then it calculates the model feature according to the face
image of the real‐time collection, and determines the identity and
confidence rate of the face image by the classifier. The recognition
technology of the embedded feature matching supports the
identification of 20‐50 people. In a certain variation range of light and
angle, the recognition accuracy rate of 20 people is greater than 90%,
the recognition accuracy rate of 50 people is greater than 80%, The
recognition technology on the server based on the deep learning
supports the recognition from 50 people to hundreds people at least,
and the recognition accuracy rate is greater than 97%.
In an embodiment of the invention, it is optional but unlimited
that, the robot has a sounding device connected to the above database,
the sounding device sends out various types of prompt tones according
to a comparative result from the face recognition module. For example,
if the face recognition module has a correct comparison, the sounding
device gets the prompt tones corresponding to the present face image in
the database, such as “Hello, Mr. Chen”. If the the regarded
identification has failed after crosschecks, the greeting application still
can sends out a general greeting without the identify information, such
as sending out a simple “Hello” by the sounding device. In an optional
embodiment, the invention can be connected to the access control
system. If the identification succeeds, the access is allowed, otherwise if
the identification fails, the access is not allowed.
In an embodiment of the invention, it is optional but unlimited
that, the image recognition system provided by the invention further
comprises a record feedback device to record and/or feed back a
comparative result from the face recognition module. It is an optional
member, the record function and the feedback function don’t need to
be implemented simultaneously. In some scenarios, only one of them is
needed.
Meanwhile, the invention also provides a recognition method by
the above‐mentioned image recognition system, comprising the steps
(a) collecting the image in the view of the robot by the image
collection module of the robot, and filling the light through a light source
as the image collection module collecting the image;
(b) using the face detection module to implement a location
process to the face image presenting in the image which is collected by
the image collection module;
(c) using the face detection module to implement a
preprocessing for the face image after being located, then comparing
with an image feature information of a known identity contained in a
database, to determine an identity information and a confidence rate of
the present face image.
If the identity information of present face image is incompatible
with an image feature information of a known identity in a database,
execute the step (a) to step (c) continually.
Figure 1 illustrates completely the operation process of the
identity recognition system: firstly, the greeting application of the robot
sends a recognition request to the image collection drive module, the
image collection drive module accepts the request, and transmits the
image sent from the camera to the face detection module. The
detection software truncates the located face image and executes the
preprocess, and then sends the processed image to the face recognition
module. The face recognition module transmits the recognition result to
the result verification module, the system executes the corresponding
operation according to the determining result. If the result is correct,
the result is sent to the greeting application, and the application utilizes
the sounding device to greet the user in the image of the camera
according to the recognized identity; if the result is wrong, the system
retransmits the recognition request to the image collection drive, and
reenters into the recognition procedure. The main point of the
determination of the recognition result verification module depends on
the confidence rate of the transmitting result of the face recognition
software. In the worst case, when the identification fails, the times of
retransmitting request is controlled by the greeting application
according to a request time out, to determine whether the request has
to be retransmitted. If the correct result is not obtained after the
identification is time out, the identification is failed. Then the greeting
application still can sends out a general greeting without identify
information, such as a simple “Hello”.
Therefore, as the invention adopts the above technical solution,
the invention does not need fixed the face pose to identify a face.
Meanwhile, the invention can identify a face based on a local or web
server database, and it increases the accuracy of the identification.
Furthermore, the face recognition procedure meets the real‐time
requirement through the suitable camera, the operation hardware
module and the operation frame.
While the present disclosure has been described in connection
with certain exemplary embodiments, it is to be understood that the
invention is not limited to the disclosed embodiments, the device and
structure, which are not specifically described, should be understood as
the common manner in the art to be implemented; any people skilled in
the art can make possible changes and modifications, or equivalents
thereof for the technical solution of the invention according to the
above method without falling out of the scope of the invention.
Therefore, the various modifications and equivalent arrangements
without departing away from the technical solution of the invention, are
included within the spirit and the scope of the technical solution of the
invention.
Claims (9)
1. An image recognition system, comprising: a robot, having an image collection module, configured to drive the image collection module to collect an image in a view of the robot by an image collection drive module; a light source configured to supplement light when the image collection module collects an image; a face detection module configured to locate a face image in the image collected by the image collection module; a face recognition module configured to implement a preprocessing for the located face image, then the preprocessed face image being compared with image feature information of a known identity contained in a database, to determine an identity information and a confidence rate of the located face image; a greeting application of the robot sends a recognition request to the image collection drive module, the image collection drive module accepts the recognition request, and drives the image collection module to collect the image and transmits the image to the face detection module; the face recognition module transmits the identity information and the confidence rate to result verification module, the system executes a corresponding operation according to a determining result as generated by the verification module; if the determining result determines the identity information is correct, the determining result is sent to the greeting application, and the greeting application utilizes a sounding device to greet user in the image of the image collection module according to a recognized identity; if the determining result determines the identity information is wrong, the system retransmits the recognition request to the image collection drive module, and reenters into a recognition procedure, the result verification module depends on the confidence rate to output the determining result.
2. The image recognition system as claimed in Claim 1, wherein the image collection module is a high definition camera, the high definition camera is capable to obtain static image and to collect at least 30 images per second; the high definition camera is connected to the robot by a MIPI or a USB interface.
3. The image recognition system as claimed in Claim 1, wherein the light source comprises an ambient light source and an infrared light source; upon utilizing the ambient light to supplement the light and collecting the image by the image collection module, if the collected image can not be recognized, the light is supplemented by the infrared light source.
4. The image recognition system as claimed in Claim 1, the preprocessing comprising: executing an angle correction treatment and a light treatment for the face image presenting in the image.
5. The image recognition system as claimed in Claim 1, wherein the database comprises a local data memory module and a web server data memory module.
6. The image recognition system as claimed in Claim 1, wherein the robot further comprises a sounding device connected to the database, the sounding device sends out various types of prompt tones according to a comparative result from the face recognition module.
7. The image recognition system as claimed in Claim 1, further comprising a record feedback device to record and/or feed back a comparative result from the face recognition module.
8. The image recognition system as claimed in Claim 1, wherein the face recognition module implements a comparison by SVM algorithm.
9. An image recognition method, using an image recognition system as claimed in any one of Claims 1‐8, comprising the steps of: (a) collecting an image in the view of the robot by the image collection module of the robot while supplementing the light by a light source; (b) using the face detection module to implement a location process to the face image presenting in the image which is collected by the image collection module; (c) using the face detection module to implement a preprocessing for the face image after being located, then comparing with an image feature information of a known identity contained in a database, to determine an identity information and a confidence rate of the located face image.
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510014262.8A CN105844202A (en) | 2015-01-12 | 2015-01-12 | Image recognition system and method |
CN201510014262.8 | 2015-01-12 | ||
PCT/CN2015/081403 WO2016112630A1 (en) | 2015-01-12 | 2015-06-12 | Image recognition system and method |
Publications (2)
Publication Number | Publication Date |
---|---|
NZ734556A NZ734556A (en) | 2020-09-25 |
NZ734556B2 true NZ734556B2 (en) | 2021-01-06 |
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