CN108073882A - Hand region recognition methods and device based on communication path - Google Patents
Hand region recognition methods and device based on communication path Download PDFInfo
- Publication number
- CN108073882A CN108073882A CN201611034826.5A CN201611034826A CN108073882A CN 108073882 A CN108073882 A CN 108073882A CN 201611034826 A CN201611034826 A CN 201611034826A CN 108073882 A CN108073882 A CN 108073882A
- Authority
- CN
- China
- Prior art keywords
- pixel
- region
- value
- hand region
- path
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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
- G06V40/107—Static hand or arm
Landscapes
- Engineering & Computer Science (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
Abstract
The present invention provides a kind of hand region recognition methods and device based on communication path, the described method includes：The steady angle value of the pixel color variation in the pixel to the shortest path and the shortest path of seed region in hand region to be identified is determined respectively, wherein the seed region is located in the hand region to be identified；Determine that the pixel is the probability value of pixel in hand region according to the distance and the steady angle value of the pixel and the seed region；Hand region is determined according to the probability value.
Description
Technical field
The present invention relates to field of image recognition, and in particular to a kind of hand region recognition methods and dress based on communication path
It puts.
Background technology
With integrating for the fast development of software and hardware relevant technical, such as wrist intelligent apparatus, smartwatch, Intelligent bracelet etc.
Spend higher and higher, function is increasingly abundanter, and the cell-phone function of significant proportion can be realized by smartwatch, Intelligent bracelet, greatly
The big method for simplifying user and receiving and transferring information.But compare with traditional smart phone, wrist intelligent apparatus is limited to small size
Display screen, on the one hand, user can not complete the operation of correlation function using touch screen or button well when in use, easily
Maloperation is caused, on the other hand, when smartwatch is worn on one on hand, to be operated on it, except waking up, dormancy etc.
Simple operations are not required the operation of another hand outer, remaining more complicated operation has the completion of another hand, can not use single
Hand independently smartwatch is operated, therefore, smartwatch on content shows and operates there are still it is very big the defects of.
The control mode based on user's hand gesture is some products provides in view of the above-mentioned problems, having at present, user can be with
By wearing the finger movement of wrist-watch come control device, principle is to utilize the photographic device acquisition hand figure set on wrist-watch
Picture, processor determine control content according to the variation of image.Such scheme needs identify the hand of user exactly from image
Portion region or profile need to reject background and other noises, only determine control content according to the variation of hand region.
Existing image identifying schemes are typically the shape feature according to target object, according to default characteristic parameter, profit
Target object is identified from image with means such as machine learning models.But this identification method resists the ability of background interference
It is poor, such as when user's local environment background is sufficiently complex, be likely to judge by accident according to shape feature, it can be seen that existing
Image identifying schemes accuracy is poor.
The content of the invention
The present invention is to solve the problem of existing image identifying schemes accuracy is poor.
In view of this, the present invention provides a kind of hand region recognition methods based on communication path, including：It determines to treat respectively
What the pixel color in the pixel to the shortest path and the shortest path of seed region in the hand region of identification changed
Steady angle value, wherein the seed region is located in the hand region to be identified；According to the pixel and the seed zone
The distance in domain and the steady angle value determine that the pixel is the probability value of pixel in hand region；It is true according to the probability value
Determine hand region.
Preferably, the pixel in hand region to be identified is determined respectively is to the shortest path of seed region and described
The steady angle value of pixel color variation on shortest path, wherein the seed region is located in the hand region to be identified
Before, further include：
Hand region to be identified is determined in the picture；
The seed region is rejected from the hand region to be identified.
Preferably, the pixel determined in hand region to be identified to seed region shortest path, including：
The pixel is calculated to the cost value in each path of the seed region, the cost value is according to the path
On the value of pixel determine；
The path with minimum cost value is chosen from each path.
Preferably, it is described to calculate the pixel to the cost value in each path of the seed region, including：
The color value of pixel on path is built into curve respectively；
Calculate the second-order partial differential coefficient of the curve；
The variance of the second order local derviation is calculated as the cost value.
Preferably, the distance and the steady angle value according to the pixel and the seed region determines the picture
Element is the probability value of pixel in hand region, including：
Determine the Euclidean distance values L of the pixel and the seed region；
Determine that the pixel is the probability value of pixel in hand region according to L and the steady angle value, wherein the probability
Value and the steady angle value correlation, the probability value and the negatively correlated relations of L.
Preferably, the hand region is determined using active contour model, and the probability value is as the active
The input value of Active contour model, the active contour model is according to the probability value, predetermined pull parameter, predetermined gravitational parameter
Hand region is obtained with predetermined initial profile.
Preferably, the steady angle value is believed according to the similarity indices of the color value under RGB, HSV and YCrCb space
The steady angle value of color change that the summation of breath determines.
Correspondingly, the present invention also provides a kind of hand region identification device based on communication path, including：
Comparing unit, for determine respectively the pixel in hand region to be identified to the shortest path of seed region and
The steady angle value of pixel color variation on the shortest path, wherein the seed region is located at the hand area to be identified
In domain；
Identifying unit, described in being determined according to the pixel with the distance of the seed region and the steady angle value
Pixel is the probability value of pixel in hand region；
Determination unit, for determining hand region according to the probability value.
Preferably, further include：
Recognition unit, for before the comparing unit is handled, determining hand region to be identified in the picture；
Culling unit, for rejecting the seed region from the hand region to be identified.
Preferably, the pixel determined in hand region to be identified to seed region shortest path, including：
Cost calculating unit, for calculating the pixel to the cost value in each path of the seed region, the generation
Value is determined according to the value of the pixel on the path；
Unit is chosen in path, for choosing the path with minimum cost value from each path.
The hand region recognition methods based on communication path provided according to embodiments of the present invention and device, by be identified
Hand region in pixel to the shortest path and the shortest path of seed region on pixel color variation it is steady
Angle value, each pixel to determine in image are the probability values of the pixel in hand region, and then according to the probability value and respectively
The distance of a pixel and presumptive area determines hand region, compared to the existing side that hand region is determined according to shape feature
Case, the embodiment of the present invention possess higher accuracy.And this programme also considers each pixel and the distance of seed region simultaneously,
And thus integrate definite above-mentioned probability value so that this programme possesses stronger antijamming capability.
Description of the drawings
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution of the prior art
Embodiment or attached drawing needed to be used in the description of the prior art are briefly described, it should be apparent that, in describing below
Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor
It puts, can also be obtained according to these attached drawings other attached drawings.
Fig. 1 is a kind of structure diagram of wearable device；
Fig. 2 is the image of the shooting of equipment shown in Fig. 1；
Fig. 3 is to carry out discoloration treated image to Fig. 2；
Fig. 4 is the flow chart of the hand region recognition methods provided in an embodiment of the present invention based on communication path；
Fig. 5 is the structure chart of the hand region identification device provided in an embodiment of the present invention based on communication path.
Specific embodiment
Technical scheme is clearly and completely described below in conjunction with attached drawing, it is clear that described implementation
Example is part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill
Personnel's all other embodiments obtained without making creative work, belong to the scope of protection of the invention.
As long as in addition, technical characteristic involved in invention described below different embodiments non-structure each other
It can be combined with each other into conflict.
An embodiment of the present invention provides a kind of hand region recognition methods based on communication path, the figure handled by this method
Seem the image shot by the wearable device with photographic device, the equipment as shown in Figure 1, wherein photographic device 01 along wearing
Person's wrist gathers wearer's hand images to palm of the hand direction.Its image collected as shown in Fig. 2, the palm of wearer in image
In integral position be more fixed, simply finger areas can become in a fixed scope with the movement of user
Change.As shown in figure 3, method provided in this embodiment includes the following steps：
S1 determines shortest path and the shortest path of the pixel to seed region in hand region to be identified respectively
The steady angle value of pixel color variation on footpath, wherein the seed region is located in the hand region to be identified；
As shown in Fig. 2, wherein comprising seed region 11,12 and second presumptive area 13 of hand region to be identified.On
The selection in above three region can preset fixed position, as long as user normally wears, seed region 11 must be used
A part for family palm, the second presumptive area 13 must not include user's palm.In order to more clearly describe the embodiment of the present invention
The each area being related to uses and Fig. 2 Fig. 4 carried out after discoloration is illustrated, it is necessary to illustrate, the embodiment of the present invention below
The color for relying on pixel is needed to carry out subsequent processing, so Fig. 4 is intended merely to clearly demonstrate given image, practical application
When need not carry out discoloration processing.
Hand region it is close as color and closing region, the shortest path of each pixel to seed region
On each pixel between color change should be subtleer and gentle, then may if there is situation about changing greatly
Represent there is the situation of interruption on path, which may not be the pixel in hand region.Therefore object pixel and seed region
Shortest path on pixel color variation smoothness it is higher, then it represents that object pixel is that the probability of hand region pixel is got over
Greatly.In this step, after analyzing the path of each pixel to seed region, a steady angle value can be obtained.
It is compared on the color value between pixel, the embodiment of the present invention can use the color value under a certain color space
It is compared, the combination of the color value under a variety of kinds of color spaces can also be used to be compared, such as can be according to RGB, HSV
And the summation of the similarity indices information of the color value under YCrCb spaces determines the similarity of two pixels, and then determine
The smoothness of pixel color variation on path.
S2 determines that the pixel is hand according to the distance and the steady angle value of the pixel and the seed region
The probability value of pixel in region.I.e. for each pixel in hand region 12 to be identified, its corresponding smoothness is utilized
Value and go out a probability value apart from COMPREHENSIVE CALCULATING with seed region (such as regional center), the probability value is more high, represents the picture
Element is that the probability in hand region is also big, on the contrary then smaller.Distance and the negatively correlated relation of probability value, the i.e. more remote then probability of distance
Value can be reduced accordingly.Such as pixel a respective distances L, smoothness w1, it is hand area that can obtain pixel a after being calculated according to L and w1
The probability of pixel is n% in domain.After the completion of all pixels COMPREHENSIVE CALCULATING, each pixel corresponds to a probability value.
S3 determines hand region according to probability value, and there are many methods of determination, such as can use simplest mode, leads to
Setting probability threshold value probability value corresponding with each pixel is crossed to compare, you can the pixel in all hand regions is filtered out, these
The summation of pixel is hand region.Preferably, in the present embodiment, a kind of active contour model may be employed (also referred to as
Snake models) identify hand region.Specifically, input value of the above-mentioned probability value as active contour model, active profile
Line model obtains in one's hands according to the corresponding probability value of each pixel, predetermined pull parameter, predetermined gravitational parameter and predetermined initial profile
Portion region.Each point on model will move to interest edges of regions under gravitation and pulling force effect, while profile keeps certain
Curvature, possess smooth characteristic.Finally, after each point movement stops, that is, the light of interest region (hand region) is identified
Sliding edge to get to be continuously smooth hand region outer profile.
The hand region recognition methods based on communication path provided according to embodiments of the present invention, passes through hand to be identified
The steady angle value of pixel color variation in pixel to the shortest path and the shortest path of seed region in region, comes
It is the probability value of the pixel in hand region to determine each pixel in image, so according to the probability value and each pixel with
The distance of presumptive area determines hand region, compared to the existing scheme that hand region is determined according to shape feature, this hair
Bright embodiment possesses higher accuracy.And this programme also considers each pixel and the distance of seed region simultaneously, and thus
To integrate definite above-mentioned probability value so that this programme possesses stronger antijamming capability.
As a preferred embodiment, before above-mentioned steps S1, can also include the following steps：
S01 determines hand region to be identified in the picture.As described above, according to the characteristics of image, hand to be identified
The position in region 12 can also be demarcated in advance, 1/2,3/4,4/5 region etc. e.g. from image border to image, specifically
Predetermined focal distance and viewfinder range when can be according to captured image determine.
S02 rejects seed region from hand region to be identified, since seed region must be a part for palm,
Therefore can this partial pixel be gone divided by be reduced calculation amount.
Above-mentioned preferred embodiment determines hand region to be identified in the picture, and must be hand region from wherein rejecting
Part so that subsequent step can be calculated just for remaining region, it is possible thereby to reduce calculation amount, improve identification effect
Rate.
Further, above-mentioned steps S1 includes the following steps：
S11 calculates pixel to the cost value in each path of seed region respectively, and cost value is according to the pixel on path
What the value of point determined；
S12 chooses the path with minimum cost value from each path.
Further, above-mentioned steps S11 may include steps of：
The color value of pixel on path is built curve by S111 respectively；
S112, the second-order partial differential coefficient of calculated curve；
S113 calculates the variance of second order local derviation as cost value.
According to above-mentioned preferred embodiment, such image upper pathway can be searched in the picture first so that object pixel
For point to the Least-cost of the center of seed region 11, the calculating of cost can be a series of based on what is passed through on image path
What the color value of pixel determined, it can calculate in the following way：The value of pixel builds a curve successively on path, calculates
The second-order partial differential coefficient of the curve counts the variance of each point second order local derviation.Variance yields is cost, it is clear that second order local derviation represents
The stationarity of the variation of road diapoint, the variance of local derviation represent the variation stationarity of picture point pixel value in whole upper pathway.
As a preferred embodiment, above-mentioned steps S2 may include steps of：
S201 determines the Euclidean distance values L of pixel and seed region；
S202 determines that pixel is the probability value of pixel in hand region according to L and the steady angle value, wherein probability value with
The steady angle value correlation, probability value and the negatively correlated relations of L.
Above-mentioned preferred embodiment integrates definite probability value using Euclidean distance and the two numerical value of smoothness value so that
This programme has stronger antijamming capability.
An alternative embodiment of the invention additionally provides a kind of device for determining hand region in the picture, as shown in figure 5,
The device includes：
Comparing unit 51, for determine respectively the pixel in hand region to be identified to seed region shortest path with
And the steady angle value of the pixel color variation on the shortest path, wherein the seed region is located at the hand to be identified
In region；
Identifying unit 52 determines institute for the distance according to the pixel and the seed region and the steady angle value
State the probability value that pixel is pixel in hand region；
Determination unit 53, for determining hand region according to the probability value.
The hand region identification device based on communication path provided according to embodiments of the present invention, passes through hand to be identified
The steady angle value of pixel color variation in pixel to the shortest path and the shortest path of seed region in region, comes
It is the probability value of the pixel in hand region to determine each pixel in image, so according to the probability value and each pixel with
The distance of presumptive area determines hand region, compared to the existing scheme that hand region is determined according to shape feature, this hair
Bright embodiment possesses higher accuracy.And this programme also considers each pixel and the distance of seed region simultaneously, and thus
To integrate definite above-mentioned probability value so that this programme possesses stronger antijamming capability.
Optionally, which can also further include：
Recognition unit 501, for before the comparing unit is handled, determining hand area to be identified in the picture
Domain；
Culling unit 502, for rejecting the seed region from the hand region to be identified.
Above-mentioned preferred embodiment determines hand region to be identified in the picture, and must be hand region from wherein rejecting
Part so that subsequent step can be calculated just for remaining region, it is possible thereby to reduce calculation amount, improve identification effect
Rate.
Optionally, comparing unit can include：
Cost calculating unit, for calculating the pixel respectively to the cost value in each path of the seed region, institute
Stating cost value is determined according to the value of the pixel on the path；
Unit is chosen in path, for choosing the path with minimum cost value from each path.
Optionally, cost calculating unit can include：
Curve construction unit, for the color value of pixel on path to be built curve respectively；
Derivative calculations unit, for calculating the second-order partial differential coefficient of the curve；
Variance computing unit, for calculating the variance of the second order local derviation as the cost value.
Optionally, identifying unit 52 can include：
Metrics calculation unit, for determining the Euclidean distance values L of the pixel and the seed region；
Probability calculation unit, for determining that the pixel is the general of pixel in hand region according to L and the steady angle value
Rate value, wherein the probability value and the steady angle value correlation, the probability value and the negatively correlated relations of L.
Above-mentioned preferred embodiment integrates definite probability value using Euclidean distance and the two numerical value of smoothness value so that
This programme has stronger antijamming capability.
Obviously, the above embodiments are merely examples for clarifying the description, and is not intended to limit the embodiments.It is right
For those of ordinary skill in the art, can also make on the basis of the above description it is other it is various forms of variation or
It changes.There is no necessity and possibility to exhaust all the enbodiments.And the obvious variation thus extended out or
Among changing still in the protection domain of the invention.
Claims (10)
1. a kind of hand region recognition methods based on communication path, which is characterized in that including：
Determine pixel in hand region to be identified to the shortest path and the shortest path of seed region respectively
The steady angle value of pixel color variation, wherein the seed region is located in the hand region to be identified；
Determine that the pixel is in hand region according to the distance and the steady angle value of the pixel and the seed region
The probability value of pixel；
Hand region is determined according to the probability value.
2. according to the method described in claim 1, it is characterized in that, determining that the pixel in hand region to be identified arrives respectively
The steady angle value of pixel color variation on the shortest path of seed region and the shortest path, wherein the seed region
Before in the hand region to be identified, further include：
Hand region to be identified is determined in the picture；
The seed region is rejected from the hand region to be identified.
3. according to the method described in claim 1, it is characterized in that, the pixel determined in hand region to be identified is to planting
The shortest path of subregion, including：
The pixel is calculated to the cost value in each path of the seed region, the cost value is according on the path
What the value of pixel determined；
The path with minimum cost value is chosen from each path.
4. according to the method described in claim 3, it is characterized in that, described calculate the pixel to each of the seed region
The cost value in path, including：
The color value of pixel on path is built into curve respectively；
Calculate the second-order partial differential coefficient of the curve；
The variance of the second order local derviation is calculated as the cost value.
5. according to the described method of any one of claim 1-4, which is characterized in that described according to the pixel and the seed
The distance in region and the steady angle value determine that the pixel is the probability value of pixel in hand region, including：
Determine the Euclidean distance values L of the pixel and the seed region；
Determine that the pixel is the probability value of pixel in hand region according to L and the steady angle value, wherein the probability value with
The steady angle value correlation, the probability value and the negatively correlated relations of L.
6. according to the method any one of claim 1-5, which is characterized in that the hand region is to utilize active profile
What line model determined, input value of the probability value as the active contour model, the active contour model according to
The probability value, predetermined pull parameter, predetermined gravitational parameter and predetermined initial profile obtain hand region.
7. according to the method any one of claim 1-6, which is characterized in that the steady angle value is according to RGB, HSV
And the steady angle value of color change that the summation of the similarity indices information of the color value under YCrCb spaces determines.
8. a kind of hand region identification device based on communication path, which is characterized in that including：
Comparing unit, for determining the pixel in hand region to be identified to the shortest path of seed region and described respectively
The steady angle value of pixel color variation on shortest path, wherein the seed region is located at the hand region to be identified
It is interior；
Identifying unit determines the pixel for the distance according to the pixel and the seed region and the steady angle value
It is the probability value of pixel in hand region；
Determination unit, for determining hand region according to the probability value.
9. device according to claim 8, which is characterized in that further include：
Recognition unit, for before the comparing unit is handled, determining hand region to be identified in the picture；
Culling unit, for rejecting the seed region from the hand region to be identified.
10. device according to claim 8, which is characterized in that the pixel determined in hand region to be identified arrives
The shortest path of seed region, including：
Cost calculating unit, for calculating the pixel to the cost value in each path of the seed region, the cost value
It is to be determined according to the value of the pixel on the path；
Unit is chosen in path, for choosing the path with minimum cost value from each path.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611034826.5A CN108073882A (en) | 2016-11-18 | 2016-11-18 | Hand region recognition methods and device based on communication path |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611034826.5A CN108073882A (en) | 2016-11-18 | 2016-11-18 | Hand region recognition methods and device based on communication path |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108073882A true CN108073882A (en) | 2018-05-25 |
Family
ID=62161200
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611034826.5A Pending CN108073882A (en) | 2016-11-18 | 2016-11-18 | Hand region recognition methods and device based on communication path |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108073882A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101144158B1 (en) * | 2010-12-20 | 2012-05-10 | 전남대학교산학협력단 | Method of lip region for lip-reading in a mobile device |
| CN104424642A (en) * | 2013-09-09 | 2015-03-18 | 华为软件技术有限公司 | Detection method and detection system for video salient regions |
| CN105184763A (en) * | 2014-06-23 | 2015-12-23 | 索尼公司 | Image processing method and device |
| CN105809651A (en) * | 2014-12-16 | 2016-07-27 | 吉林大学 | Image saliency detection method based on edge non-similarity comparison |
-
2016
- 2016-11-18 CN CN201611034826.5A patent/CN108073882A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101144158B1 (en) * | 2010-12-20 | 2012-05-10 | 전남대학교산학협력단 | Method of lip region for lip-reading in a mobile device |
| CN104424642A (en) * | 2013-09-09 | 2015-03-18 | 华为软件技术有限公司 | Detection method and detection system for video salient regions |
| CN105184763A (en) * | 2014-06-23 | 2015-12-23 | 索尼公司 | Image processing method and device |
| CN105809651A (en) * | 2014-12-16 | 2016-07-27 | 吉林大学 | Image saliency detection method based on edge non-similarity comparison |
Non-Patent Citations (1)
| Title |
|---|
| 谭立新等: "《智能家居机器人设计与控制》", 31 January 2015, 北京理工大学出版社 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11546505B2 (en) | Touchless photo capture in response to detected hand gestures | |
| US10496163B2 (en) | Eye and head tracking | |
| US11531402B1 (en) | Bimanual gestures for controlling virtual and graphical elements | |
| US20220206588A1 (en) | Micro hand gestures for controlling virtual and graphical elements | |
| US20160259980A1 (en) | Systems and methodologies for performing intelligent perception based real-time counting | |
| US20220051441A1 (en) | Multi-camera cross reality device | |
| US20170045950A1 (en) | Gesture Recognition Systems | |
| US20110193778A1 (en) | Device and method for controlling mouse pointer | |
| JP4238278B2 (en) | Adaptive tracking of gesture interfaces | |
| CN107077593A (en) | For the enhanced system and method for display screen | |
| CN107368810A (en) | Method for detecting human face and device | |
| EP3922011A1 (en) | Lightweight and low power cross reality device with high temporal resolution | |
| US11889209B2 (en) | Lightweight cross reality device with passive depth extraction | |
| KR20150127381A (en) | Method for extracting face feature and apparatus for perforimg the method | |
| CN109155053A (en) | Information processing equipment, information processing method and recording medium | |
| KR102181897B1 (en) | Device and method for mobile tooltip using eye detecting | |
| JP2019109843A (en) | Classification device, classification method, attribute recognition device, and machine learning device | |
| US10713847B2 (en) | Method and device for interacting with virtual objects | |
| CN106933341B (en) | Method and device for determining region of finger in image and wrist type equipment | |
| CN108073935A (en) | Method and device based on adjacent pixels and communication path identification hand region | |
| CN108073271A (en) | Method and device based on presumptive area identification hand region | |
| CN108073871A (en) | Method and device based on two kinds of presumptive area identification hand regions | |
| CN108073882A (en) | Hand region recognition methods and device based on communication path | |
| CN108073878A (en) | Method and device based on presumptive area and communication path identification hand region | |
| CN108073870A (en) | Method and device based on seed region and communication path identification hand region |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180525 |
|
| RJ01 | Rejection of invention patent application after publication |