CN104125386A - Image processing apparatus and image processing method - Google Patents
Image processing apparatus and image processing method Download PDFInfo
- Publication number
- CN104125386A CN104125386A CN201310147584.0A CN201310147584A CN104125386A CN 104125386 A CN104125386 A CN 104125386A CN 201310147584 A CN201310147584 A CN 201310147584A CN 104125386 A CN104125386 A CN 104125386A
- Authority
- CN
- China
- Prior art keywords
- image
- processor
- receiver
- angle
- gai
- 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.)
- Granted
Links
Landscapes
- Image Processing (AREA)
- Image Analysis (AREA)
- Editing Of Facsimile Originals (AREA)
Abstract
The invention brings forward an image processing apparatus and its image processing method. The image processing device contains a processor which is used for segmenting a raw image into multiple cluster images and rotating each cluster image an angle to generate an output image.
Description
Technical field
The invention relates to a kind of image processor and image treatment method thereof.More specifically, a raw video is divided into multiple groups image by image processor of the present invention, and each group image is rotated to an angle, to produce an image output.
Background technology
For example, along with popularizing of image capture unit (: the hand-held device of camera, video recorder and any loading image acquisition module), people can record the dribs and drabs in life by image capture unit.
For example, the member in meeting takes down notes record notes separately by paper conventionally.After meeting adjourned; if member wants to obtain other members' notes; conventionally can use image capture unit to capture one by one the image of each notes; or once capture the image of whole notes, and then the image that this is comprised to whole notes is given each notes to be divided into multiple images one by one with operation image processing software by manual type.
But the above-mentioned practice is inconvenience and consuming time all quite, when particularly conference member is considerable.In view of this, how providing more convenient image capture and image processing mechanism, allow user can more directly and quickly obtain the image of each notes, is industry problem demanding prompt solution.
Summary of the invention
The object of the present invention is to provide a kind of image processor and image treatment method thereof.Image processor is multiple groups images by an Image Segmentation that comprises multiple notes, the wherein corresponding notes of each group image.Subsequently, these group's images are rotated respectively an angle by image processor, to produce an image output.Thus, image output is to show each notes of rectifying, and reads for user.
For achieving the above object, the present invention proposes a kind of image processor, and it comprises a processor.This processor is in order to a raw video is divided into multiple groups image, and Ge Gai group image is rotated to an angle, to produce an image output.
In addition, the present invention more proposes a kind of image treatment method, and it is applicable to an image processor, and it comprises a processor.This processor is carried out this image treatment method.This image treatment method comprises step: (a) raw video is divided into multiple groups image; And (b) Ge Gai group image is rotated to an angle, to produce an image output.
Brief description of the drawings
For above-mentioned purpose of the present invention, feature and advantage can be become apparent, below in conjunction with accompanying drawing, the specific embodiment of the present invention is elaborated, wherein:
Fig. 1 is the schematic diagram of the image processor 1 of first embodiment of the invention;
Fig. 2 A to 2C describes respectively raw video 102, group's image 104 and the image output 106 of the first embodiment;
Fig. 3 is the schematic diagram of the image processor 3 of second embodiment of the invention;
Fig. 4 is the schematic diagram of the image processor 4 of third embodiment of the invention; And
Fig. 5 is the flow chart of the image treatment method of fourth embodiment of the invention.
Main element symbol description:
1 image processor
3 image processors
4 image processors
11 processors
13 receivers
13 image acquisition modules
102 raw videos
104 group's images
106 image outputs
Embodiment
The present invention mainly relates to a kind of image processor and image treatment method thereof.It should be noted that, following examples are in order to illustrate technology contents of the present invention, not in order to limit the scope of the invention.Moreover in following examples and accompanying drawing, element unrelated to the invention has omitted and has not illustrated, and in graphic, each interelement size relationship is only for asking easy understanding, non-in order to limit actual ratio.
As shown in Figure 1, it is the schematic diagram of an image processor 1 to the first embodiment of the present invention.Image processor 1 comprises a processor 11.Image processor 1 can be a camera, a video camera, a smart mobile phone or arbitrary device with image processing ability.
A raw video 102 is divided into multiple groups image 104 by processor 11.Subsequently, each group image is rotated to an angle, to produce an image output 106.Particularly, raw video 102 is images that comprise multiple independent notes, as shown in Figure 2 A.Processor 102 is analyzed raw video 102, to be divided into multiple groups image 104, as shown in Figure 2 B.Finally, each group image 104 is rotated an angle by processor 11, so that it is proper, and produces image output 106(as shown in Figure 2 C), read for a user.
How following declarative description processor 11 is divided into one of these group's images 104 by raw video 102 is implemented aspect.Conventionally nearer based on each notes described content distance to each other, first, raw video 102 is converted to a grayscale image by processor 11, and grayscale image two-value is turned to a binaryzation image.Then, processor 11, based on the one 8 adjacent algorithms (8-neighbor connectivity algorithm) that are communicated with, is multiple parts by binaryzation Image Segmentation.Due to the 8 adjacent known technologies that are communicated with calculation this area owned by France, therefore not in this to go forth.
Subsequently, processor 11, according to the Euclidean distance between each several part (Euclidean distance), is divided into multiple groups by these parts, and according to these groups, produces these group's images 104.In detail, processor 11 is Euclidean distances of calculating between each several part, if the Euclidean distance between some part is less than a preset value, these parts is attributed to same group.
In addition, implement in aspect in another, the processor 11 more record content based on difference notes should use the pen of different colours to write, so that raw video 102 is divided into multiple parts.First, processor 11 is analyzed multiple line colors of raw video 102, and according to these line colors, raw video 102 is divided into multiple parts.Then, according to the Euclidean distance between each several part, these parts are divided into multiple groups, and according to these groups, produce these group's images 104.
In addition, implement in aspect in another, the processor 11 more record content based on difference notes should use the pen of different line weights to write, so that raw video 102 is divided into multiple parts.First, processor 11 is analyzed multiple line weights of raw video 102, and according to these line weights, raw video 102 is divided into multiple parts.Then, according to the Euclidean distance between each several part, these parts are divided into multiple groups, and according to these groups, produce these group's images 104.
How following declarative description processor 11 rotates one of an angle by each group image 104 is implemented aspect.First, each group image 104 is carried out an optics character identification by processor 11, to identify multiple characters, and according to a character presentation direction of these characters of Ge Gai group image, determines the angle of the each group of rotation image 104.In detail, owing to writing common can carrying out by along continuous straight runs, thus after character is identified, can obtain the horizontal direction of notes, to obtain the angle of rotation.
In addition, implement in aspect in another, processor 11 can detect the grid in each group image 104, and according to the grid of each group image 104, determines the angle of the each group of rotation image 104.In detail, if notes system writes in the paper with grid, be upright shape based on grid, therefore can obtain the angle of rotation.
In addition, implement in aspect in another, processor 11 can carry out each group image 104 an optics character identification, to identify multiple characters, and according to one of these characters of each group image 104 lines around, determines the angle of the each group of rotation image 104.In detail, the emphasis mark of word and the mode of mark can be generally to horizontal line owing to writing conventionally, therefore after character is identified, can, according to these characters horizontal line around, obtain the angle of rotation.
As shown in Figure 2, it is the schematic diagram of an image processor 2 to the second embodiment of the present invention.In the present embodiment, image processor 2, except comprising processor 11, more comprises a receiver 13, and it is electrically connected to processor 11.
In following declarative description the present embodiment, how processor 11 is divided into one of group's image 104 by raw video 102 is implemented aspect.If there are one or more cameras (figure does not illustrate) in meeting room, meeting room content environment is taken, to obtain one or more environmental images, receiver 13 can receive at least one environmental images from least one camera, and processor 11 can detect the multiple faces (face) at least one environmental images, and according to these faces, determine the angle of the each group of rotation image 104.
Except detecting face, processor 11 ground desirable and generation detects the multiple hands (hand) at least one environmental images, and according to these hands, determines the angle of the each group of rotation image 104.Moreover processor 11 also ground desirable and generation detects the multiple pens (pen) at least one environmental images, and according to these pens, determine the angle of the each group of rotation image 104.
In addition, implement in aspect in another, if there are one or more directional microphones (figure does not illustrate) in meeting room, meeting room content environment is recorded, to obtain one or more multiple sound beam directions, receiver 13 more can receive multiple sound beam direction information from least one directional microphone, and processor 11 more can be according to these sound beam direction information, determines the angle of the each group of rotation image 104.
In addition, implement in aspect in another, if the upper surface of the desk of writing for personnel in meeting room is a contact surface plate, the touching of hand while writing with sensing everyone, receiver 13 can more receive multiple sensing signals from contact surface plate, and wherein each sensing signal is that an action of writing that responds a user produces.In the case, processor 11 more can be according to these sensing signals, determine the angle of the each group of rotation image 104.
In addition, be different from the first embodiment, in the present embodiment, receiver 13 can receive raw video 102 from an image capture unit (figure does not illustrate), processes for processor 14.Image capture unit can be the hand-held device of a camera, a video camera or arbitrary any loading image acquisition module.
As shown in Figure 3, it is the schematic diagram of an image processor 3 to the third embodiment of the present invention.In the present embodiment, image processor 3, except comprising processor 11 and receiver 13, more comprises an image acquisition module 15, and it is electrically connected to processor 11.In the present embodiment, raw video 102 is captured by image acquisition module 15, processes, but not received from an image capture unit by receiver 13 for processor 14.In originally executing in example, image processor 1 can be a camera, a video camera, and has smart mobile phone or arbitrary device with image processing ability and image acquisition module of image acquisition module.
As shown in Figure 5, it is the flow chart of an image treatment method of the present invention to the fourth embodiment of the present invention.Image treatment method is the image processor for comprising a processor, as the image processor 1 of the first embodiment, as the image processor 3 of the second embodiment and as the image processor 4 of the 3rd embodiment.Image treatment method processor is performed.
First,, in step S501, a raw video is divided into multiple groups image.Then, in step S503, each group image is rotated to an angle, to produce an image output.Except above-mentioned steps, the 4th embodiment also can carry out the first embodiment, the second embodiment and the described all operations of the 3rd embodiment and function, under technical field those of ordinary skill can be directly acquainted with image treatment method of the present invention how based on above-mentioned the first embodiment, the second embodiment and the 3rd embodiment to carry out these operations and function, therefore do not repeat them here.
In sum, image processor of the present invention can be by an image that comprises multiple notes, analyzes and the part of the each notes of correspondence is divided and rotated, to produce a proper image output.Thus, the invention provides one image capture and image processing mechanism more easily, allow user can more directly and quickly obtain the image of each notes.
It should be noted that, the above embodiments are only in order to disclose enforcement aspect of the present invention, and explain technical characterictic of the present invention, are not used for limiting protection category of the present invention.In addition, any be familiar with this operator can unlabored change or the arrangement of isotropism all belong to the scope that the present invention advocates, and protection scope of the present invention should be as the criterion with claims.
Claims (28)
1. an image processor, comprises:
One processor, in order to a raw video is divided into multiple groups image, and rotates an angle by Ge Gai group image, to produce an image output.
2. image processor as claimed in claim 1, also comprises a receiver, is electrically connected to this processor, in order to receive this raw video from an image capture unit.
3. image processor as claimed in claim 1, also comprises an image acquisition module, is electrically connected to this processor, in order to capture this raw video.
4. image processor as claimed in claim 1, is characterized in that, this processor also in order to:
This raw video is converted to a grayscale image;
This grayscale image two-value is turned to a binaryzation image;
Based on the one 8 adjacent algorithms (8-neighbor connectivity algorithm) that are communicated with, be multiple parts by this binaryzation Image Segmentation;
According to the each Euclidean distance between this part (Euclidean distance), described part is divided into multiple groups; And
According to described group, produce described group image.
5. image processor as claimed in claim 1, is characterized in that, this processor also in order to:
Analyze multiple line colors of this raw video;
According to described line color, this raw video is divided into multiple parts;
According to the each Euclidean distance between this part, described part is divided into multiple groups; And
According to described group, produce described group image.
6. image processor as claimed in claim 1, is characterized in that, this processor also in order to:
Analyze multiple line weights of this raw video;
According to described line weight, this raw video is divided into multiple parts;
According to the each Euclidean distance between this part, described part is divided into multiple groups; And
According to described group, produce described group image.
7. image processor as claimed in claim 1, also comprise a receiver, be electrically connected to this processor, wherein this receiver is also in order to receive at least one environmental images from least one camera, and this processor is more in order to detect the multiple faces (face) in this at least one environmental images, and according to described face, determine this angle of rotation Ge Gai group image.
8. image processor as claimed in claim 1, also comprise a receiver, be electrically connected to this processor, wherein this receiver is also in order to receive at least one environmental images from least one camera, and this processor is also in order to detect the multiple hands (hand) in this at least one environmental images, and according to described hand, determine this angle of rotation Ge Gai group image.
9. image processor as claimed in claim 1, it is characterized in that, this processor is also in order to carry out Ge Gai group image one optics character identification, to identify multiple characters, and according to a character book direction of the described character of Ge Gai group image, determine this angle of rotation Ge Gai group image.
10. image processor as claimed in claim 1, also comprise a receiver, be electrically connected to this processor, wherein this receiver is also in order to receive at least one environmental images from least one camera, and this processor is also in order to detect the multiple pens (pen) in this at least one environmental images, and according to described pen, determine this angle of rotation Ge Gai group image.
11. image processors as claimed in claim 1, is characterized in that, this processor is also in order to detect the grid in Ge Gai group image, and according to this grid of Ge Gai group image, this angle of Ge Gai group image is rotated in decision.
12. image processors as claimed in claim 1, also comprise a receiver, be electrically connected to this processor, wherein this receiver is also in order to receive multiple sound beam direction information from least one directional microphone, and this processor also, in order to according to described sound beam direction information, determines this angle of rotation Ge Gai group image.
13. image processors as claimed in claim 1, it is characterized in that, this processor is also in order to Ge Gai group image is carried out to an optics character identification, to identify multiple characters, and according to one of the described character of Ge Gai group image lines around, determine this angle of rotation Ge Gai group image.
14. image processors as claimed in claim 1, also comprise a receiver, be electrically connected to this processor, this receiver is also in order to receive multiple sensing signals from a contact surface plate, this contact surface plate is arranged at the upper surface of a desk, respectively this sensing signal is that an action of writing that responds a user produces, and this processor is also in order to according to described sensing signal, determines this angle of rotation Ge Gai group image.
15. 1 kinds of image treatment methods for an image processor, this image processor comprises a processor, and this image treatment method is performed and comprise the following step by this processor:
(a) raw video is divided into multiple groups image; And
(b) Ge Gai group image is rotated to an angle, to produce an image output.
16. image treatment methods as claimed in claim 15, is characterized in that, this image processor also comprises a receiver, are electrically connected to this processor, and in the front the following step that also comprises of this step (a):
Make this receiver receive this raw video from an image capture unit.
17. image treatment methods as claimed in claim 15, is characterized in that, this image processor also comprises an image acquisition module, are electrically connected to this processor, and in the front the following step that also comprises of this step (a):
Make this image acquisition module capture this raw video.
18. image treatment methods as claimed in claim 15, is characterized in that, step (a) also comprises the following step:
(a1) this raw video is converted to a grayscale image;
(a2) this grayscale image two-value is turned to a binaryzation image;
(a3) based on the one 8 adjacent algorithms that are communicated with, be multiple parts by this binaryzation Image Segmentation;
(a4) the respectively Euclidean distance between this part of basis, is divided into multiple groups by described part; And
(a5), according to described group, produce described group image.
19. image treatment methods as claimed in claim 15, is characterized in that, step (a) also comprises the following step:
(a1) analyze multiple line colors of this raw video;
(a2), according to described line color, this raw video is divided into multiple parts;
(a3) the respectively Euclidean distance between this part of basis, is divided into multiple groups by described part; And
(a4), according to described group, produce described group image.
20. image treatment methods as claimed in claim 15, is characterized in that, step (a) also comprises the following step:
(a1) analyze multiple line weights of this raw video;
(a2), according to described line weight, this raw video is divided into multiple parts;
(a3) the respectively Euclidean distance between this part of basis, is divided into multiple groups by described part; And
(a4), according to described group, produce described group image.
21. image treatment methods as claimed in claim 15, is characterized in that, this image processor also comprises a receiver, and this step (b) also comprises:
(b1) make this receiver receive at least one environmental images from least one camera;
(b2) detect the multiple faces (face) in this at least one environmental images; And
(b3), according to described face, determine this angle of rotation Ge Gai group image.
22. image treatment methods as claimed in claim 15, is characterized in that, this image processor also comprises a receiver, and this step (b) also comprises:
(b1) make this receiver receive at least one environmental images from least one camera;
(b2) detect the multiple hands (hand) in this at least one environmental images; And
(b3), according to described hand, determine this angle of rotation Ge Gai group image.
23. image treatment methods as claimed in claim 15, is characterized in that, this step (b) also comprises:
(b1) Ge Gai group image is carried out to an optics character identification, to identify multiple characters; And
(b2), according to a character presentation direction of the described character of Ge Gai group image, determine this angle of rotation Ge Gai group image.
24. image treatment methods as claimed in claim 15, is characterized in that, this image processor also comprises a receiver, and this step (b) also comprises:
(b1) make this receiver receive at least one environmental images from least one camera;
(b2) detect the multiple pens (pen) in this at least one environmental images; And
(b3), according to described pen, determine this angle of rotation Ge Gai group image.
25. image treatment methods as claimed in claim 15, is characterized in that, this step (b) also comprises:
(b1) detect the grid in Ge Gai group image; And
(b2), according to this grid of Ge Gai group image, determine this angle of rotation Ge Gai group image.
26. image treatment methods as claimed in claim 15, is characterized in that, this image processor also comprises a receiver, and this step (b) also comprises:
(b1) make this receiver receive at least one sound beam direction information from least one directional microphone; And
(b2), according to this at least one sound beam direction information, determine respectively this angle of this at least one group image of rotation.
27. image treatment methods as claimed in claim 15, is characterized in that, this step (b) also comprises:
(b1) Ge Gai group image is carried out to an optics character identification, to identify multiple characters; And
(b2), according to one of the described character of Ge Gai group image lines around, determine this angle of rotation Ge Gai group image.
28. image treatment methods as claimed in claim 15, is characterized in that, this image processor also comprises a receiver, and this step (b) also comprises:
(b1) make this receiver receive multiple sensing signals from a contact surface plate, this contact surface plate is arranged at the upper surface of a desk, and respectively this sensing signal is that an action of writing that responds a user produces; And
(b2), according to described sensing signal, determine this angle of rotation Ge Gai group image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310147584.0A CN104125386B (en) | 2013-04-25 | 2013-04-25 | Image processor and its image treatment method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310147584.0A CN104125386B (en) | 2013-04-25 | 2013-04-25 | Image processor and its image treatment method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104125386A true CN104125386A (en) | 2014-10-29 |
| CN104125386B CN104125386B (en) | 2018-04-17 |
Family
ID=51770640
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310147584.0A Active CN104125386B (en) | 2013-04-25 | 2013-04-25 | Image processor and its image treatment method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104125386B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI714926B (en) * | 2018-01-29 | 2021-01-01 | 開曼群島商創新先進技術有限公司 | Method for constructing dream reproduction model, method and device for dream reproduction |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1259713A (en) * | 1998-11-27 | 2000-07-12 | 英业达集团(西安)电子技术有限公司 | Portable equipment for taking photograph and reading and its operating method |
| CN101426068A (en) * | 2007-11-01 | 2009-05-06 | 宏达国际电子股份有限公司 | Method for image display |
| CN101499253A (en) * | 2008-01-28 | 2009-08-05 | 宏达国际电子股份有限公司 | Output picture regulation method and apparatus |
| CN102494733A (en) * | 2011-12-12 | 2012-06-13 | 西安电子科技大学 | Water level monitoring system based on image processing and method |
| CN102663337A (en) * | 2012-03-16 | 2012-09-12 | 江南大学 | Method for quick Data Matrix two-dimensional barcode identifying under simple condition background |
| CN102737381A (en) * | 2012-06-13 | 2012-10-17 | 西安电子科技大学 | Image partitioning method based on mixed bipartite graph clustering integration |
| CN102737367A (en) * | 2012-06-17 | 2012-10-17 | 四川农业大学 | Tea image enhancement and division method based on color characteristic |
| CN102831419A (en) * | 2012-07-27 | 2012-12-19 | 中国科学院自动化研究所 | Method for detecting and blurring plate number in street view image rapidly |
| CN102999247A (en) * | 2011-07-07 | 2013-03-27 | 宏达国际电子股份有限公司 | Methods and systems for displaying interfaces |
| CN103020941A (en) * | 2012-12-28 | 2013-04-03 | 昆山市工业技术研究院有限责任公司 | Panoramic stitching based rotary camera background establishment method and panoramic stitching based moving object detection method |
| CN103049738A (en) * | 2012-12-07 | 2013-04-17 | 北京中邮致鼎科技有限公司 | Method for segmenting multiple vehicles connected through shadows in video |
-
2013
- 2013-04-25 CN CN201310147584.0A patent/CN104125386B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1259713A (en) * | 1998-11-27 | 2000-07-12 | 英业达集团(西安)电子技术有限公司 | Portable equipment for taking photograph and reading and its operating method |
| CN101426068A (en) * | 2007-11-01 | 2009-05-06 | 宏达国际电子股份有限公司 | Method for image display |
| CN101499253A (en) * | 2008-01-28 | 2009-08-05 | 宏达国际电子股份有限公司 | Output picture regulation method and apparatus |
| CN102999247A (en) * | 2011-07-07 | 2013-03-27 | 宏达国际电子股份有限公司 | Methods and systems for displaying interfaces |
| CN102494733A (en) * | 2011-12-12 | 2012-06-13 | 西安电子科技大学 | Water level monitoring system based on image processing and method |
| CN102663337A (en) * | 2012-03-16 | 2012-09-12 | 江南大学 | Method for quick Data Matrix two-dimensional barcode identifying under simple condition background |
| CN102737381A (en) * | 2012-06-13 | 2012-10-17 | 西安电子科技大学 | Image partitioning method based on mixed bipartite graph clustering integration |
| CN102737367A (en) * | 2012-06-17 | 2012-10-17 | 四川农业大学 | Tea image enhancement and division method based on color characteristic |
| CN102831419A (en) * | 2012-07-27 | 2012-12-19 | 中国科学院自动化研究所 | Method for detecting and blurring plate number in street view image rapidly |
| CN103049738A (en) * | 2012-12-07 | 2013-04-17 | 北京中邮致鼎科技有限公司 | Method for segmenting multiple vehicles connected through shadows in video |
| CN103020941A (en) * | 2012-12-28 | 2013-04-03 | 昆山市工业技术研究院有限责任公司 | Panoramic stitching based rotary camera background establishment method and panoramic stitching based moving object detection method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI714926B (en) * | 2018-01-29 | 2021-01-01 | 開曼群島商創新先進技術有限公司 | Method for constructing dream reproduction model, method and device for dream reproduction |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104125386B (en) | 2018-04-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9280694B2 (en) | Decoding machine-readable optical codes with aesthetic component | |
| CN109684980B (en) | Automatic scoring method and device | |
| US11683468B2 (en) | Coordination of multiple structured light-based 3D image detectors | |
| CN104484643A (en) | Intelligent identification method and system for hand-written table | |
| US20130330003A1 (en) | Adaptive thresholding for image recognition | |
| WO2015188556A1 (en) | Multi-cue fusion based ticket positioning recognition method and system | |
| CN109598162A (en) | Identify method, apparatus, terminal device and the storage medium of two dimensional code | |
| US20160188950A1 (en) | Optical fingerprint recognition device | |
| CN102163108B (en) | Method and device for identifying multiple touch points | |
| JP6326847B2 (en) | Image processing apparatus, image processing method, and image processing program | |
| CN104881238A (en) | Touch control display device and touch control method thereof | |
| JP6739937B2 (en) | Information processing apparatus, control method of information processing apparatus, and program | |
| CN108446036B (en) | Intelligent writing equipment and intelligent writing system | |
| WO2014180387A1 (en) | Information input method and device | |
| CN103399629A (en) | Method and device for capturing gesture displaying coordinates | |
| CN104615231A (en) | Determination method for input information, and equipment | |
| CN111401242B (en) | Credential detection method, apparatus, electronic device and storage medium | |
| US20120048936A1 (en) | Method for reading code displayed on printed matter | |
| CN104125386A (en) | Image processing apparatus and image processing method | |
| CN103914186A (en) | Image location recognition system | |
| CN110658929A (en) | Control method and device for intelligent pen | |
| CN204719733U (en) | A kind of touch control display apparatus | |
| US20150049945A1 (en) | Image processing apparatus and image processing method | |
| US10248214B2 (en) | Wearable device for writing and drawing | |
| CN114359923A (en) | Certificate character recognition method and device, computer and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |