CN105096330A - Image processing method capable of automatically recognizing pure-color borders, system and a photographing terminal - Google Patents
Image processing method capable of automatically recognizing pure-color borders, system and a photographing terminal Download PDFInfo
- Publication number
- CN105096330A CN105096330A CN201510514843.8A CN201510514843A CN105096330A CN 105096330 A CN105096330 A CN 105096330A CN 201510514843 A CN201510514843 A CN 201510514843A CN 105096330 A CN105096330 A CN 105096330A
- Authority
- CN
- China
- Prior art keywords
- pure color
- color frame
- row
- image
- edge
- 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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
- G06T2207/20132—Image cropping
Landscapes
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The invention discloses an image processing method capable of automatically recognizing pure-color borders, a system capable of automatically recognizing pure-color borders and a photographing terminal. The method includes the following steps that: edge extraction is performed on a to-be-processed image provided with pure-color borders, so that an edge image can be obtained; the edge image is put into row-and-column pixel statistics, so that the number of edge pixels in each row and each column can be obtained, and the positions of pixels of edge regions of the rows and columns can be calculated, so that the positions of the pure-color borders can be obtained; and the size of an image region inside the pure-color borders is calculated according to the positions of the pure-color borders. Thus, the original size of the to-be-processed image can be restored, and references can be provided for follow-up operation such as thumbnail display. With the processing process of the method adopted, the pure-color borders of a common to-be-processed image can be automatically identified, and the pure-color borders of a to-be-processed image onto which a filter or a material is added can be also intelligently identified. The method has a wide application range.
Description
Technical field
The present invention relates to technical field of image processing, particularly a kind of image processing method of automatic identification pure color frame and system, the camera terminal of application the method thereof.
Background technology
Popular along with square photo and square video, causing image all can be made by the frame adding pure color in advance before processed is not that the image of 1:1 ratio is well retained, this new picture mode not only provide the user a new mode of finding a view, also more convenient user is by photo upload to social platform simultaneously, and user is without the need to carrying out cutting again.
But the image that with the addition of frame may produce various inharmonic situation in subsequent treatment or application process, after needing again to remove frame, conveniently subsequent treatment could be carried out.Such as photograph album is when obtaining square photo or square video carries out thumbnail displaying, this thumbnail and other will be caused not to add the image thumbnails of frame obviously different, visual experience is uncomfortable, and adding due to pure color frame, what cause the thumbnail of image to be shown is the content of whole image, although entirety all show, also less, cause the main body that will express also to be weakened.
Summary of the invention
The present invention is for solving the problem, provide a kind of image processing method of automatic identification pure color frame, system and camera terminal, it is by identifying pure color frame, thus reduces the original size of pending image, can provide reference for associative operations such as follow-up thumbnail displayings.
For achieving the above object, the technical solution used in the present invention is:
First, the invention provides a kind of image processing method of automatic identification pure color frame, it comprises the following steps:
10. obtain the pending image with pure color frame, and edge extracting is carried out to pending image, obtain outline map;
The capable pixel with arranging of outline map described in 20. pairs is added up, and obtains the statistics number of every a line and edge pixel point that each arranges;
30. calculate row and the position of the most border area pixels point of row according to the statistics number of described edge pixel point, obtain the position of pure color frame;
40. according to the size of the image-region within this pure color frame of position calculation of described pure color frame.
Preferably, in described step 10, edge extracting is carried out to pending image and obtains outline map, comprise further:
11. pairs of pending images carry out gray proces and obtain gray-scale map;
12. pairs of gray-scale maps carry out edge extracting, obtain outline map.
Preferably, carry out edge extracting in described step 12 to gray-scale map, it adopts the combination of any one edge detection algorithm following or more than one edge detection algorithm: Canny algorithm, Sobel algorithm, Prewitt algorithm, Roberts algorithm.
Preferably, in described step 20, to described outline map, the capable pixel with arranging is added up, and its statistical method comprises further:
Each row of outline map described in 21. pairs carries out the statistics of number of edges:
The statistics number of this row of initialization is 0, travels through all pixels of this row successively, if be edge pixel point, adding up number adds 1, finally obtains the statistics number of the edge pixel point of this row;
Each row of outline map described in 22. pairs carry out the statistics of number of edges:
The statistics number of these row of initialization is 0, travels through all pixels of these row successively, if be edge pixel point, adding up number adds 1, finally obtains the statistics number of the edge pixel point of these row.
Preferably, calculate the position of row and the most border area pixels point of row according to the statistics number of described edge pixel point in described step 30, by carrying out threshold decision to the statistics number of described edge pixel point respectively from the two ends end to end of row or column, if the statistics number of current row or column does not exceed threshold value continue the judgement of next line or next column until have a line or have the statistics number of row to exceed described threshold value, then orientate this row maybe head of these row or most fringe region of tail as, thus obtain the position of pure color frame.
Preferably, according to the size of the image-region within this pure color frame of the position calculation of described pure color frame in described step 40, its computing formula is:
RowWidth＝RowRight-RowLeft；
ColHeight＝ColBottom-ColTop；
Wherein, RowRight, RowLeft are respectively the position of the head of the row of described pure color frame, the most border area pixels point at tail two ends, ColBottom, ColTop are respectively the position of the head of the row of described pure color frame, the most border area pixels point at tail two ends, and RowWidth, ColHeight are the width, highly of image-region within described pure color frame.
Preferably, according to the size of the image-region within this pure color frame of the position calculation of described pure color frame in described step 40, and carry out thumbnail displaying according to the image-region within described pure color frame further, it is by carrying out cutting process to the image-region within pure color frame, the pure color frame removing image obtains original image, and shows according to this original image acquisition thumbnail.
Secondly, the present invention also provides a kind of image processing system of automatic identification pure color frame, and it comprises:
Edge extracting module, it obtains the pending image with pure color frame, and carries out edge extracting to pending image, obtains outline map;
Pixels statistics module, its to described outline map the capable pixel with arranging add up, obtain the statistics number of every a line and edge pixel point that each arranges;
Position computation module, it calculates row and the position of the most border area pixels point of row according to the statistics number of described edge pixel point, obtains the position of pure color frame;
Size calculation module, it is according to the size of the image-region within this pure color frame of the position calculation of described pure color frame.
Preferably, also comprise gradation processing module, described pending image is undertaken after gray proces obtains gray-scale map by this gradation processing module, then carries out edge extracting by described edge extracting module to described gray-scale map, obtains outline map.
In addition, the present invention also provides a kind of camera terminal, it is characterized in that, this camera terminal comprises the image processing system automatically identifying pure color frame as above.
Preferably, described camera terminal comprises: mobile phone, digital camera or panel computer.
The invention has the beneficial effects as follows:
The image processing method of a kind of automatic identification pure color frame of the present invention, system and camera terminal, it obtains outline map by carrying out edge extracting to the pending image with pure color frame, then to described outline map, the capable pixel with arranging is added up, obtain the statistics number of every a line and edge pixel point that each arranges, and calculate the position that row and the position of the most border area pixels point of row obtain pure color frame thus, finally according to the size of the image-region within this pure color frame of position calculation of this pure color frame, thus reduce the original size of pending image, reference can be provided for operations such as follow-up thumbnail displayings, and adopt the processing procedure of said method automatically can not only identify the pure color frame of common pending image, but also Intelligent Recognition can with the addition of the pure color frame of the pending image of filter or material, the scope of application is wider.
Accompanying drawing explanation
Accompanying drawing described herein is used to provide a further understanding of the present invention, forms a part of the present invention, and schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the general flow chart that the present invention identifies the image processing method of pure color frame automatically;
Fig. 2 is the Size calculation schematic diagram of the image-region within the pure color frame of the pending image of the present invention;
Fig. 3 is the structural representation that the present invention identifies the image processing system of pure color frame automatically;
Fig. 4 is the structural representation of camera terminal of the present invention.
Embodiment
For making the object of the embodiment of the present invention, technical scheme and advantage clearly, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, instead of whole embodiments.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
As shown in Figure 1, the image processing method of a kind of automatic identification pure color frame of the present invention, it comprises the following steps:
10. obtain the pending image with pure color frame, and edge extracting is carried out to pending image, obtain outline map;
The capable pixel with arranging of outline map described in 20. pairs is added up, and obtains the statistics number of every a line and edge pixel point that each arranges;
30. calculate row and the position of the most border area pixels point of row according to the statistics number of described edge pixel point, obtain the position of pure color frame;
40. according to the size of the image-region within this pure color frame of position calculation of described pure color frame.
In described step 10, edge extracting is carried out to pending image and obtains outline map, comprise further:
11. pairs of pending images carry out gray proces and obtain gray-scale map;
12. pairs of gray-scale maps carry out edge extracting, obtain outline map.
The computing formula of the gray proces in above-mentioned steps 11 is:
GRAY＝0.299*RED+0.587*GREEN+0.114*BLUE；
Or
GRAY＝(RED*306+GREEN*601+BLUE*117+512)/1024；
Wherein, GRAY is the gray-scale value of the corresponding pixel points of gray-scale map; RED, GREEN, BLUE are respectively the color value of the red, green, blue passage of the corresponding pixel points of pending image.
Carry out edge extracting to gray-scale map in above-mentioned steps 12, it adopts the combination of any one edge detection algorithm following or more than one edge detection algorithm: Canny algorithm, Sobel algorithm, Prewitt algorithm, Roberts algorithm; Each algorithm is simply described below:
Canny algorithm is a multistage optimized algorithm with filtering, enhancing, detection, before processing, first Canny algorithm utilizes Gaussian filter to carry out smoothed image to remove denoising, then the finite difference of single order local derviation is adopted to assign to compute gradient amplitude and direction, in processing procedure, also by the process through a non-maxima suppression, two threshold values are finally adopted to connect edge.
Sobel algorithm be the form of filter operator to extract edge, X, Y-direction respectively uses a template, and two form assemblies are got up formation 1 gradient algorithm, and X-direction template has the greatest impact to vertical edge, and Y-direction template has the greatest impact to horizontal edge.
Prewitt algorithm is Weighted Average Algorithm, has inhibiting effect to noise, but pixel is on average equivalent to carry out low-pass filtering to image,
Robert algorithm is a kind of gradient algorithm, and it, by the differential representation gradient of intersecting, is a kind of algorithm utilizing local difference algorithm to find edge, best to the image effect with precipitous low noise.
In described step 20, to described outline map, the capable pixel with arranging is added up, and its statistical method comprises further:
Each row of outline map described in 21. pairs carries out the statistics of number of edges:
The statistics number of this row of initialization is 0, travels through all pixels of this row successively, if be edge pixel point, adding up number adds 1, finally obtains the statistics number of the edge pixel point of this row;
Each row of outline map described in 22. pairs carry out the statistics of number of edges:
The statistics number of these row of initialization is 0, travels through all pixels of these row successively, if be edge pixel point, adding up number adds 1, finally obtains the statistics number of the edge pixel point of these row.
Calculate the position of row and the most border area pixels point of row according to the statistics number of described edge pixel point in described step 30, by carrying out threshold decision to the statistics number of described edge pixel point respectively from the two ends end to end of row or column, if the statistics number of current row or column does not exceed threshold value continue the judgement of next line or next column until have a line or have the statistics number of row to exceed described threshold value, then orientate this row maybe head of these row or most fringe region of tail as, thus obtain the position of pure color frame.
As shown in Figure 2, according to the size of the image-region (i.e. original image region) within this pure color frame of the position calculation of described pure color frame in described step 40, its computing formula is:
RowWidth＝RowRight-RowLeft；
ColHeight＝ColBottom-ColTop；
Wherein, RowRight, RowLeft are respectively the position of the head of the row of described pure color frame, the most border area pixels point at tail two ends, ColBottom, ColTop are respectively the position of the head of the row of described pure color frame, the most border area pixels point at tail two ends, and RowWidth, ColHeight are the width, highly of image-region within described pure color frame.
As preferred embodiment, according to the size of the image-region within this pure color frame of the position calculation of described pure color frame in described step 40, and carry out thumbnail displaying according to the image-region within described pure color frame further, it is by carrying out cutting process to the image-region within pure color frame, the pure color frame removing image obtains original image, and shows according to this original image acquisition thumbnail.The thumbnail obtained by said method be one complete, without the image of frame, thus can the content of exploded view picture to a greater degree.
As shown in Figure 3, the present invention also provides a kind of image processing system 100 of automatic identification pure color frame, and it comprises:
Edge extracting modules A, it obtains the pending image with pure color frame, and carries out edge extracting to pending image, obtains outline map;
Pixels statistics module B, its to described outline map the capable pixel with arranging add up, obtain the statistics number of every a line and edge pixel point that each arranges;
Position computation module C, it calculates row and the position of the most border area pixels point of row according to the statistics number of described edge pixel point, obtains the position of pure color frame;
Size calculation module D, it is according to the size of the image-region within this pure color frame of the position calculation of described pure color frame.
In addition, also comprise gradation processing module E, described pending image is undertaken after gray proces obtains gray-scale map by this gradation processing module E, then carries out edge extracting by described edge extracting modules A to described gray-scale map, obtains outline map.
As shown in Figure 4, the present invention also provides a kind of camera terminal 200, this camera terminal 200 comprises the image processing system 100 automatically identifying pure color frame as above, wherein, described image processing system 100 can adopt the structure of Fig. 3 embodiment, and it accordingly, the technical scheme of embodiment of the method shown in Fig. 1 can be performed, it realizes principle and technique effect is similar, see the relevant record in above-described embodiment, can repeat no more in detail herein.
Described camera terminal comprises: mobile phone, digital camera or panel computer etc. are configured with the equipment of camera.
It should be noted that, pure color frame of the present invention can be the pure color frame of dark border or white frame or other random colors, and described frame might not be confined to square frame, be applicable to rectangle frame, circular frame, oval frame, polygon frame too, or the frame of other arbitrary shapes.
Each embodiment in this instructions all adopts the mode of going forward one by one to describe, and what each embodiment stressed is the difference with other embodiments, between each embodiment identical similar part mutually see.For system embodiment and terminal embodiment, due to itself and embodiment of the method basic simlarity, so description is fairly simple, relevant part illustrates see the part of embodiment of the method.And, in this article, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thus make to comprise the process of a series of key element, method, article or equipment and not only comprise those key elements, but also comprise other key elements clearly do not listed, or also comprise by the intrinsic key element of this process, method, article or equipment.When not more restrictions, the key element limited by statement " comprising ... ", and be not precluded within process, method, article or the equipment comprising described key element and also there is other identical element.In addition, one of ordinary skill in the art will appreciate that all or part of step realizing above-described embodiment can have been come by hardware, the hardware that also can carry out instruction relevant by program completes, described program can be stored in a kind of computer-readable recording medium, the above-mentioned storage medium mentioned can be ROM (read-only memory), disk or CD etc.
Above-mentioned explanation illustrate and describes the preferred embodiments of the present invention, be to be understood that the present invention is not limited to the form disclosed by this paper, should not regard the eliminating to other embodiments as, and can be used for other combinations various, amendment and environment, and can in invention contemplated scope herein, changed by the technology of above-mentioned instruction or association area or knowledge.And the change that those skilled in the art carry out and change do not depart from the spirit and scope of the present invention, then all should in the protection domain of claims of the present invention.
Claims (11)
1. automatically identify an image processing method for pure color frame, it is characterized in that, comprise the following steps:
10. obtain the pending image with pure color frame, and edge extracting is carried out to pending image, obtain outline map;
The capable pixel with arranging of outline map described in 20. pairs is added up, and obtains the statistics number of every a line and edge pixel point that each arranges;
30. calculate row and the position of the most border area pixels point of row according to the statistics number of described edge pixel point, obtain the position of pure color frame;
40. according to the size of the image-region within this pure color frame of position calculation of described pure color frame.
2. the image processing method of a kind of automatic identification pure color frame according to claim 1, is characterized in that: carry out edge extracting to pending image in described step 10 and obtain outline map, comprise further:
11. pairs of pending images carry out gray proces and obtain gray-scale map;
12. pairs of gray-scale maps carry out edge extracting, obtain outline map.
3. the image processing method of a kind of automatic identification pure color frame according to claim 2, it is characterized in that: carry out edge extracting to gray-scale map in described step 12, it adopts the combination of any one edge detection algorithm following or more than one edge detection algorithm: Canny algorithm, Sobel algorithm, Prewitt algorithm, Roberts algorithm.
4. the image processing method of a kind of automatic identification pure color frame according to claim 1 or 2 or 3, is characterized in that: in described step 20, to described outline map, the capable pixel with arranging is added up, and its statistical method comprises further:
Each row of outline map described in 21. pairs carries out the statistics of number of edges:
The statistics number of this row of initialization is 0, travels through all pixels of this row successively, if be edge pixel point, adding up number adds 1, finally obtains the statistics number of the edge pixel point of this row;
Each row of outline map described in 22. pairs carry out the statistics of number of edges:
The statistics number of these row of initialization is 0, travels through all pixels of these row successively, if be edge pixel point, adding up number adds 1, finally obtains the statistics number of the edge pixel point of these row.
5. the image processing method of a kind of automatic identification pure color frame according to claim 1 or 2 or 3, it is characterized in that: the position calculating row and the most border area pixels point of row in described step 30 according to the statistics number of described edge pixel point, by carrying out threshold decision to the statistics number of described edge pixel point respectively from the two ends end to end of row or column, if the statistics number of current row or column does not exceed threshold value continue the judgement of next line or next column until have a line or have the statistics number of row to exceed described threshold value, then orientate this row maybe head of these row or most fringe region of tail as, thus obtain the position of pure color frame.
6. the image processing method of a kind of automatic identification pure color frame according to claim 1 or 2 or 3, it is characterized in that: according to the size of the image-region within this pure color frame of the position calculation of described pure color frame in described step 40, its computing formula is:
RowWidth＝RowRight-RowLeft；
ColHeight＝ColBottom-ColTop；
Wherein, RowRight, RowLeft are respectively the position of the head of the row of described pure color frame, the most border area pixels point at tail two ends, ColBottom, ColTop are respectively the position of the head of the row of described pure color frame, the most border area pixels point at tail two ends, and RowWidth, ColHeight are the width, highly of image-region within described pure color frame.
7. the image processing method of a kind of automatic identification pure color frame according to claim 1 or 2 or 3, it is characterized in that: according to the size of the image-region within this pure color frame of the position calculation of described pure color frame in described step 40, and carry out thumbnail displaying according to the image-region within described pure color frame further, it is by carrying out cutting process to the image-region within pure color frame, the pure color frame removing image obtains original image, and shows according to this original image acquisition thumbnail.
8. automatically identify an image processing system for pure color frame, it is characterized in that, comprising:
Edge extracting module, it obtains the pending image with pure color frame, and carries out edge extracting to pending image, obtains outline map;
Pixels statistics module, its to described outline map the capable pixel with arranging add up, obtain the statistics number of every a line and edge pixel point that each arranges;
Position computation module, it calculates row and the position of the most border area pixels point of row according to the statistics number of described edge pixel point, obtains the position of pure color frame;
Size calculation module, it is according to the size of the image-region within this pure color frame of the position calculation of described pure color frame.
9. the image processing system of a kind of automatic identification pure color frame according to claim 8, it is characterized in that: also comprise gradation processing module, described pending image is undertaken after gray proces obtains gray-scale map by this gradation processing module, by described edge extracting module, edge extracting is carried out to described gray-scale map again, obtain outline map.
10. a camera terminal, is characterized in that, comprises the image processing system of the automatic identification pure color frame described in any one of claim 8 to 9.
11. camera terminals according to claim 10, is characterized in that, described camera terminal comprises: mobile phone, digital camera or panel computer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510514843.8A CN105096330A (en) | 2015-08-20 | 2015-08-20 | Image processing method capable of automatically recognizing pure-color borders, system and a photographing terminal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510514843.8A CN105096330A (en) | 2015-08-20 | 2015-08-20 | Image processing method capable of automatically recognizing pure-color borders, system and a photographing terminal |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105096330A true CN105096330A (en) | 2015-11-25 |
Family
ID=54576669
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510514843.8A Pending CN105096330A (en) | 2015-08-20 | 2015-08-20 | Image processing method capable of automatically recognizing pure-color borders, system and a photographing terminal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105096330A (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106409193A (en) * | 2016-07-08 | 2017-02-15 | 深圳市华星光电技术有限公司 | Display screen blur detection system and method thereof |
| CN106570483A (en) * | 2016-11-07 | 2017-04-19 | 厦门市妖猫网络有限公司 | Image positioning method and system |
| CN107123127A (en) * | 2017-04-27 | 2017-09-01 | 北京京东尚科信息技术有限公司 | A kind of image subject extracting method and device |
| CN107800949A (en) * | 2016-09-05 | 2018-03-13 | 北京小米移动软件有限公司 | The method and device of image in a kind of shooting frame |
| CN108416789A (en) * | 2018-06-04 | 2018-08-17 | 武汉斑马快跑科技有限公司 | Method for detecting image edge and system |
| CN108965692A (en) * | 2018-06-15 | 2018-12-07 | Oppo广东移动通信有限公司 | Paster setting method and device |
| CN109302595A (en) * | 2018-10-29 | 2019-02-01 | 镇江智米网络科技有限公司 | A kind of Atomatic focusing method and projection device of hotel's projection device |
| CN109348198A (en) * | 2018-10-29 | 2019-02-15 | 镇江智米网络科技有限公司 | A kind of control method and projection device of hotel's projection device |
| CN109766530A (en) * | 2018-12-13 | 2019-05-17 | 东软集团股份有限公司 | Generation method, device, storage medium and the electronic equipment of chart frame |
| CN112017203A (en) * | 2019-05-31 | 2020-12-01 | 广州市百果园信息技术有限公司 | Image processing method, video processing method, device, equipment and storage medium |
| CN114037096A (en) * | 2021-10-29 | 2022-02-11 | 河南格林循环电子废弃物处置有限公司 | Automatic household appliance identification and marking device and use method thereof |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090256924A1 (en) * | 2008-04-09 | 2009-10-15 | Hon Hai Precision Industry Co., Ltd. | Image capture device capable of combining images and print method thereof |
| CN104240228A (en) * | 2013-06-24 | 2014-12-24 | 阿里巴巴集团控股有限公司 | Detecting method and device for specific pictures applied to website |
-
2015
- 2015-08-20 CN CN201510514843.8A patent/CN105096330A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090256924A1 (en) * | 2008-04-09 | 2009-10-15 | Hon Hai Precision Industry Co., Ltd. | Image capture device capable of combining images and print method thereof |
| CN104240228A (en) * | 2013-06-24 | 2014-12-24 | 阿里巴巴集团控股有限公司 | Detecting method and device for specific pictures applied to website |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106409193A (en) * | 2016-07-08 | 2017-02-15 | 深圳市华星光电技术有限公司 | Display screen blur detection system and method thereof |
| CN107800949A (en) * | 2016-09-05 | 2018-03-13 | 北京小米移动软件有限公司 | The method and device of image in a kind of shooting frame |
| CN106570483A (en) * | 2016-11-07 | 2017-04-19 | 厦门市妖猫网络有限公司 | Image positioning method and system |
| CN107123127A (en) * | 2017-04-27 | 2017-09-01 | 北京京东尚科信息技术有限公司 | A kind of image subject extracting method and device |
| CN108416789A (en) * | 2018-06-04 | 2018-08-17 | 武汉斑马快跑科技有限公司 | Method for detecting image edge and system |
| CN108965692B (en) * | 2018-06-15 | 2021-03-09 | Oppo广东移动通信有限公司 | Sticker setting method and device |
| CN108965692A (en) * | 2018-06-15 | 2018-12-07 | Oppo广东移动通信有限公司 | Paster setting method and device |
| CN109302595A (en) * | 2018-10-29 | 2019-02-01 | 镇江智米网络科技有限公司 | A kind of Atomatic focusing method and projection device of hotel's projection device |
| CN109348198A (en) * | 2018-10-29 | 2019-02-15 | 镇江智米网络科技有限公司 | A kind of control method and projection device of hotel's projection device |
| CN109766530A (en) * | 2018-12-13 | 2019-05-17 | 东软集团股份有限公司 | Generation method, device, storage medium and the electronic equipment of chart frame |
| CN109766530B (en) * | 2018-12-13 | 2023-07-07 | 东软集团股份有限公司 | Method and device for generating chart frame, storage medium and electronic equipment |
| CN112017203A (en) * | 2019-05-31 | 2020-12-01 | 广州市百果园信息技术有限公司 | Image processing method, video processing method, device, equipment and storage medium |
| CN114037096A (en) * | 2021-10-29 | 2022-02-11 | 河南格林循环电子废弃物处置有限公司 | Automatic household appliance identification and marking device and use method thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105096330A (en) | Image processing method capable of automatically recognizing pure-color borders, system and a photographing terminal | |
| WO2016206087A1 (en) | Low-illumination image processing method and device | |
| Pei et al. | Removing rain and snow in a single image using saturation and visibility features | |
| Kim et al. | Optimized contrast enhancement for real-time image and video dehazing | |
| US8335394B2 (en) | Image processing method for boundary resolution enhancement | |
| US11138695B2 (en) | Method and device for video processing, electronic device, and storage medium | |
| CN105243371A (en) | Human face beauty degree detection method and system and shooting terminal | |
| KR102084343B1 (en) | Background removal | |
| JP2016505186A (en) | Image processor with edge preservation and noise suppression functions | |
| CN111145105B (en) | Image rapid defogging method and device, terminal and storage medium | |
| CN107256539B (en) | Image sharpening method based on local contrast | |
| CN104766307A (en) | Picture processing method and device | |
| CN104010114B (en) | Video denoising method and device | |
| CN109598736A (en) | The method for registering and device of depth image and color image | |
| CN108234826B (en) | Image processing method and device | |
| CN111062331A (en) | Mosaic detection method and device for image, electronic equipment and storage medium | |
| CN109285122A (en) | A kind of method and apparatus carrying out image procossing | |
| CN108304840B (en) | Image data processing method and device | |
| US20200065949A1 (en) | Image processing method and device | |
| CN104504712B (en) | Image processing method and device | |
| US8693769B2 (en) | Image classification methods and systems | |
| Qi et al. | Image dehazing based on structure preserving | |
| WO2017128646A1 (en) | Image processing method and device | |
| CN111414877B (en) | Table cutting method for removing color frame, image processing apparatus and storage medium | |
| Lai et al. | Single image dehazing with optimal transmission map |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20151125 |