CN104851114A - Method for partial color changing of image, and terminal - Google Patents
Method for partial color changing of image, and terminal Download PDFInfo
- Publication number
- CN104851114A CN104851114A CN201510200800.2A CN201510200800A CN104851114A CN 104851114 A CN104851114 A CN 104851114A CN 201510200800 A CN201510200800 A CN 201510200800A CN 104851114 A CN104851114 A CN 104851114A
- Authority
- CN
- China
- Prior art keywords
- image
- target location
- haar
- rgb value
- color
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
-
- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
Landscapes
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Color Image Communication Systems (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses a method for partial color changing of an image, and a terminal. The method includes the steps of identifying a target position, to be changed partially in color, of a generated image; detecting the RGB value of the identified target position; and changing the RGB value of the target position, and obtaining an image with the target position the color of which is changed to be a preset color. Disclosed is also the corresponding terminal. The target position, to be changed partially in color, of the generated image is identified, and then is changed in color, so the same target position in the same image can be shot in different colors. In this way, the photographing fun is improved.
Description
Technical field
The present invention relates to picture imaging techniques field, particularly relate to a kind of method and the terminal that realize image local variable color.
Background technology
Current intelligent terminal such as mobile phone, panel computer etc. all have camera function, but, present intelligent terminal is used to take pictures, it is exactly any color that what color that to be all subject itself be takes pictures out, even through photo aftertreatment, in color, also just increase and decrease saturation degree etc., and variable color can not be carried out to the local location of subject, the photo taken namely cannot be allowed to take different colors to same target location.
Summary of the invention
The invention provides a kind of method and the terminal that realize image local variable color, to make the same target location in same image can take different colors, increase the interest of shooting.
On the one hand, provide a kind of method realizing image local variable color, comprising:
Identify the target location for the treatment of local discolouration in the image generated;
Detect the rgb value of the target location identified;
Convert the rgb value of described target location, the colour switching obtaining described target location becomes the image of pre-set color.
On the other hand, provide a kind of terminal, comprising:
First recognition unit, for identify generation image in treat the target location of local discolouration;
Detecting unit, for detecting the rgb value of the target location identified;
First converter unit, for converting the rgb value of described target location, the colour switching obtaining described target location becomes the image of pre-set color.
Visible, according to a kind of method and terminal realizing image local variable color provided by the invention, the target location of local discolouration is treated in the image generated by identification, then colour switching is carried out to this target location, the same target location in same image can be made can to take different colors, increase the interest of shooting.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
A kind of schematic flow sheet realizing the method for image local variable color that Fig. 1 provides for the embodiment of the present invention;
Fig. 2 is the image treating local discolouration of example;
Fig. 3 realizes the schematic flow sheet of the method for image local variable color for another kind that the embodiment of the present invention provides;
Fig. 4 is the schematic diagram of the original rectangular feature of the acquisition Haar-like feature of example;
The structural representation of a kind of terminal that Fig. 5 provides for the embodiment of the present invention;
The structural representation of the another kind of terminal that Fig. 6 provides for the embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.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.
If the photo that the color that user can make to appear at same position is upon taking a picture different is selected to store for user, that will be an interesting experience.The invention provides a kind of method and the terminal that realize image local variable color, the target location of local discolouration is treated in the image generated by identification, then colour switching is carried out to this target location, the same target location in same image can be made can to take different colors, increase the interest of shooting.
Below in conjunction with Fig. 1-Fig. 4, the method realizing image local variable color that the embodiment of the present invention provides is described in detail:
Refer to Fig. 1, be a kind of schematic flow sheet realizing the method for image local variable color that the embodiment of the present invention provides, the method comprises the following steps:
Step S101, identifies the target location for the treatment of local discolouration in the image generated.
The present embodiment carries out variable color to the local location of the image generated, and key to identify the target location for the treatment of local discolouration.As the image treating local discolouration of Fig. 2 example, target location or the target object that carry out local discolouration are this trees, and the color on sky and meadow does not change.Such as, Haar classifier algorithm can be applied image is identified, obtain the target location for the treatment of variable color.
Step S102, detects the rgb value of the target location identified.
Namely the change of color is to obtain color miscellaneous to the change of red (R), green (G), blue (B) three Color Channels and their superpositions each other.Before turn colors, first to detect the rgb value that the target location of identifying image is original.
Step S103, converts the rgb value of described target location, and the colour switching obtaining described target location becomes the image of pre-set color.
According to the color wanting to obtain, carry out the calculating of rgb value, then the rgb value of target location is converted, namely convert the color obtaining wanting to obtain, and the rgb value outside the target location of this image is not changed, thus realize the local discolouration of image.Such as, the tree in Fig. 2 can be transformed into shades of colour, instead of green originally in image, and the color on sky and meadow does not change, user can select the photo that the color of one or more tree preserved wherein is different, increases the interest of shooting.
According to a kind of method realizing image local variable color that the embodiment of the present invention provides, the target location of local discolouration is treated in the image generated by identification, then colour switching is carried out to this target location, the same target location in same image can be made can to take different colors, increase the interest of shooting.
Refer to Fig. 3, the another kind provided for the embodiment of the present invention realizes the schematic flow sheet of the method for image local variable color, and the method comprises the following steps:
Obtain the strong classifier distinguishing described target location and non-targeted position after the Haar feature of step S201, application AdaBoost Algorithm for Training sample, all strong classifiers of screening cascade are Haar classifier.
Step S202, the Haar feature applying described Haar classifier carries out the identification of described target location.
Step S203, in identifying, utilizes the calculating of integrogram algorithm to the Haar feature of described Haar classifier to accelerate.
Step S201-S203 identifies image for application Haar classifier algorithm, obtains the concrete steps treating the target location of variable color.
HAAR characteristic method is that the local feature data sample by obtaining under being used in the external conditions such as various different scenes is cultivated, the sorter of the corresponding topical feature obtained, when carrying out local feature and detecting, by searching coupling in sorter, determine whether corresponding feature, thus realize detecting local feature.Overall operation steps is as follows:
Haar classifier=Haar-like feature+integrogram method+AdaBoost+ cascade.
1.Haar-like feature:
Any one rectangle in Fig. 4 is put on the region of inspected object, then, by the pixel of white portion and deduct black region pixel and, the value obtained we be referred to as object features value, you are put into a non-inspected object region this rectangle, and the eigenwert so calculated should be different with object features value.
2. integrogram method:
Often run into a picture sample, often run into a sub-video in window, we are faced with the problem how calculating current subimage eigenwert, how a Haar-like feature arranges and can better embody detection clarification of objective in a window, this is unknown, so just will train, and before training, we can only pass through the exhaustive all such features of permutation and combination, only for the most basic four features, in the window of a 24 × 24size arbitrary arrangement at least can produce number in 100,000 feature, be very large to the calculated amount of these feature evaluations.And integrogram be exactly only traversal image just can obtain all area pixel in image and fast algorithm, improve the efficiency of image feature value calculating greatly.
Wherein, step S203 can comprise the following steps:
A: calculate the cumulative of pixel line direction;
B: described image of lining by line scan, the cumulative value obtaining integral image of each described pixel line direction of recursive calculation;
C: image configuration goes out integral image according to the scan value of described integral image;
D: calculated by the Haar feature of described integral image to described Haar classifier.
3.AdaBoost：
What kind of is combined to one piece and can better distinguishes target to be detected and non-targeted to determine which type of rectangular characteristic.
4. cascade:
Exactly the combination that Adaboost forms all is cascaded up, improve accuracy rate.
Step S204, detects the rgb value of the target location identified.
Namely the change of color is to obtain color miscellaneous to the change of red (R), green (G), blue (B) three Color Channels and their superpositions each other.Before turn colors, first to detect the rgb value that the target location of identifying image is original.
Step S205, is transformed to the rgb value corresponding with pre-set color to the rgb value of data corresponding to the target location in the yuv data of the image of described generation, obtains the yuv data after converting.
Step S206, according to the yuv data after described conversion, exports the image of setting form.
Before output picture or image, what the sensor of camera exported is yuv data, and namely the rgb value of conversion target location is convert the rgb value of data corresponding to the target location in yuv data.According to the color wanting to obtain, carry out the calculating of rgb value, then the rgb value of target location is converted, namely convert the color obtaining wanting to obtain, and the rgb value outside the target location of this image is not changed, thus realize the local discolouration of image.Such as, the tree in Fig. 2 can be transformed into shades of colour, instead of green originally in image, and the color on sky and meadow does not change, user can select the photo that the color of one or more tree preserved wherein is different, increases the interest of shooting.After the RGB of target location is converted, obtain the yuv data after converting rgb value, yuv data is pressed into the image of setting form, outputs to photograph album.
According to a kind of method realizing image local variable color that the embodiment of the present invention provides, the target location of local discolouration is treated in the image generated by identification, then colour switching is carried out to this target location, the same target location in same image can be made can to take different colors, increase the interest of shooting; Adopt Haar classifier to carry out the identification of target location, screening type cascade system improves the accuracy rate of sorter, and the use of integrogram algorithm accelerates the speed of algorithm.
Below in conjunction with Fig. 5-Fig. 6, the terminal realizing image local variable color that the embodiment of the present invention provides is described in detail:
Refer to Fig. 5, be the structural representation of a kind of terminal that the embodiment of the present invention provides, this terminal 1000 comprises:
First recognition unit 11, for identify generation image in treat the target location of local discolouration.
The present embodiment carries out variable color to the local location of the image generated, and key is that the first recognition unit 11 will identify the target location for the treatment of local discolouration.As the image treating local discolouration of Fig. 2 example, target location or the target object that carry out local discolouration are this trees, and the color on sky and meadow does not change.Such as, Haar classifier algorithm can be applied image is identified, obtain the target location for the treatment of variable color.
Detecting unit 12, detects the rgb value of the target location identified.
Namely the change of color is to obtain color miscellaneous to the change of red (R), green (G), blue (B) three Color Channels and their superpositions each other.Before turn colors, first detecting unit 12 will detect the original rgb value in the target location of identifying image.
First converter unit 13, for converting the rgb value of described target location, the colour switching obtaining described target location becomes the image of pre-set color.
First converter unit 13 is according to the color wanting to obtain, carry out the calculating of rgb value, then the rgb value of target location is converted, namely convert the color obtaining wanting to obtain, and the rgb value outside the target location of this image is not changed, thus realize the local discolouration of image.Such as, the tree in Fig. 2 can be transformed into shades of colour, instead of green originally in image, and the color on sky and meadow does not change, user can select the photo that the color of one or more tree preserved wherein is different, increases the interest of shooting.
According to a kind of terminal that the embodiment of the present invention provides, the target location of local discolouration is treated in the image generated by identification, then colour switching is carried out to this target location, the same target location in same image can be made can to take different colors, increase the interest of shooting.
Refer to Fig. 6, be the structural representation of the another kind of terminal that the embodiment of the present invention provides, this terminal 2000 comprises:
First recognition unit 21, identifies image for applying Haar classifier algorithm, obtains the target location for the treatment of variable color.
Particularly, the first recognition unit 21 comprises Haar classifier training unit 211, second recognition unit 212 and accelerates recognition unit 213.
Haar classifier training unit 211, for apply AdaBoost Algorithm for Training sample Haar feature after obtain distinguishing the strong classifier of described target location and non-targeted position, all strong classifiers of screening cascade are Haar classifier.
Second recognition unit 212, the Haar feature for applying described Haar classifier carries out the identification of described target location.
Accelerate recognition unit 213, in identifying, utilize the calculating of integrogram algorithm to the Haar feature of described Haar classifier to accelerate.
HAAR characteristic method is that the local feature data sample by obtaining under being used in the external conditions such as various different scenes is cultivated, the sorter of the corresponding topical feature obtained, when carrying out local feature and detecting, by searching coupling in sorter, determine whether corresponding feature, thus realize detecting local feature.Overall operation is as follows:
Haar classifier=Haar-like feature+integrogram method+AdaBoost+ cascade.
1.Haar-like feature:
Any one rectangle in Fig. 4 is put on the region of inspected object, then, by the pixel of white portion and deduct black region pixel and, the value obtained we be referred to as object features value, you are put into a non-inspected object region this rectangle, and the eigenwert so calculated should be different with object features value.
2. integrogram method:
Often run into a picture sample, often run into a sub-video in window, we are faced with the problem how calculating current subimage eigenwert, how a Haar-like feature arranges and can better embody detection clarification of objective in a window, this is unknown, so just will train, and before training, we can only pass through the exhaustive all such features of permutation and combination, only for the most basic four features, in the window of a 24 × 24size arbitrary arrangement at least can produce number in 100,000 feature, be very large to the calculated amount of these feature evaluations.And integrogram be exactly only traversal image just can obtain all area pixel in image and fast algorithm, improve the efficiency of image feature value calculating greatly.
Wherein, accelerate recognition unit 213 and can comprise the first computing unit, the second computing unit, integral image tectonic element and the 3rd computing unit.Wherein:
First computing unit: for calculating the cumulative of pixel line direction;
Second computing unit: for described image of lining by line scan, the cumulative value obtaining integral image of each described pixel line direction of recursive calculation;
Integral image tectonic element, goes out integral image for image configuration according to the scan value of described integral image;
3rd computing unit, for calculating by the Haar feature of described integral image to described Haar classifier.
3.AdaBoost：
What kind of is combined to one piece and can better distinguishes target to be detected and non-targeted to determine which type of rectangular characteristic.
4. cascade:
Exactly the combination that Adaboost forms all is cascaded up, improve accuracy rate.
Detecting unit 22, for detecting the rgb value of the target location identified.
Namely the change of color is to obtain color miscellaneous to the change of red (R), green (G), blue (B) three Color Channels and their superpositions each other.Before turn colors, first to detect the rgb value that the target location of identifying image is original.
First converter unit 23, for converting the rgb value of described target location, the colour switching obtaining described target location becomes the image of pre-set color.
In the present embodiment, the first converter unit 23 comprises the second converter unit 231 and output unit 232.
Second converter unit 231, the rgb value for data corresponding to the target location in the yuv data of the image to described generation is transformed to the rgb value corresponding with pre-set color, obtains the yuv data after converting.
Output unit 232, for according to the yuv data after described conversion, exports the image of setting form.
Before output picture or image, what the sensor of camera exported is yuv data, and namely the rgb value of conversion target location is convert the rgb value of data corresponding to the target location in yuv data.According to the color wanting to obtain, carry out the calculating of rgb value, then the rgb value of target location is converted, namely convert the color obtaining wanting to obtain, and the rgb value outside the target location of this image is not changed, thus realize the local discolouration of image.Such as, the tree in Fig. 2 can be transformed into shades of colour, instead of green originally in image, and the color on sky and meadow does not change, user can select the photo that the color of one or more tree preserved wherein is different, increases the interest of shooting.After the RGB of target location is converted, obtain the yuv data after converting rgb value, yuv data is pressed into the image of setting form, outputs to photograph album.
According to a kind of terminal that the embodiment of the present invention provides, the target location of local discolouration is treated in the image generated by identification, then colour switching is carried out to this target location, the same target location in same image can be made can to take different colors, increase the interest of shooting; Adopt Haar classifier to carry out the identification of target location, screening type cascade system improves the accuracy rate of sorter, and the use of integrogram algorithm accelerates the speed of algorithm.
It should be noted that, for aforesaid each embodiment of the method, in order to simple description, therefore it is all expressed as a series of combination of actions, but those skilled in the art should know, the present invention is not by the restriction of described sequence of movement, because according to the present invention, some step can adopt other orders or carry out simultaneously.Secondly, those skilled in the art also should know, the embodiment described in instructions all belongs to preferred embodiment, and involved action and module might not be that the present invention is necessary.
In the above-described embodiments, the description of each embodiment is all emphasized particularly on different fields, in certain embodiment, there is no the part described in detail, can see the associated description of other embodiments.
Through the above description of the embodiments, those skilled in the art can be well understood to the present invention can use hardware implementing, or firmware realizes, or their array mode realizes.When implemented in software, above-mentioned functions can be stored in computer-readable medium or as the one or more instruction on computer-readable medium or code and transmit.Computer-readable medium comprises computer-readable storage medium and communication media, and wherein communication media comprises any medium being convenient to transmit computer program from a place to another place.Storage medium can be any usable medium that computing machine can access.As example but be not limited to: computer-readable medium can comprise random access memory (Random Access Memory, RAM), ROM (read-only memory) (Read-Only Memory, ROM), EEPROM (Electrically Erasable Programmable Read Only Memo) (Electrically ErasableProgrammable Read-Only Memory, EEPROM), read-only optical disc (Compact Disc Read-OnlyMemory, or other optical disc storage CD-ROM), magnetic disk storage medium or other magnetic storage apparatus, or the program code that can be used in carrying or storing the expectation with instruction or data structure form also can by any other medium of computer access.In addition.Any connection can be suitable become computer-readable medium.Such as, if software uses concentric cable, optical fiber cable, twisted-pair feeder, Digital Subscriber Line (Digital SubscriberLine, DSL) or the wireless technology of such as infrared ray, radio and microwave and so on from website, server or other remote source, so the wireless technology of concentric cable, optical fiber cable, twisted-pair feeder, DSL or such as infrared ray, wireless and microwave and so on be included in affiliated medium fixing in.As used in the present invention, dish (Disk) and dish (disc) comprise compression laser disc (CD), laser dish, laser disc, Digital Versatile Disc (DVD), floppy disk and Blu-ray Disc, the usual magnetic of its mid-game copy data, what dish then carried out optics with laser copies data.Combination above also should be included within the protection domain of computer-readable medium.
In a word, the foregoing is only the preferred embodiment of technical solution of the present invention, be not intended to limit protection scope of the present invention.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. realize a method for image local variable color, it is characterized in that, comprising:
Identify the target location for the treatment of local discolouration in the image generated;
Detect the rgb value of the target location identified;
Convert the rgb value of described target location, the colour switching obtaining described target location becomes the image of pre-set color.
2. the method for claim 1, is characterized in that, treats the target location of local discolouration, comprising in the image that described identification generates:
Application Haar classifier algorithm identifies described image, treats the target location of variable color described in acquisition.
3. method as claimed in claim 2, it is characterized in that, described application Haar classifier algorithm identifies described image, treats the target location of variable color, comprising described in acquisition:
Obtain the strong classifier distinguishing described target location and non-targeted position after the Haar feature of application AdaBoost Algorithm for Training sample, all strong classifiers of screening cascade are Haar classifier;
The Haar feature applying described Haar classifier carries out the identification of described target location;
In identifying, the calculating of integrogram algorithm to the Haar feature of described Haar classifier is utilized to accelerate.
4. method as claimed in claim 3, is characterized in that, described in identifying, utilizes the calculating of integrogram algorithm to the Haar feature of described Haar classifier to accelerate, comprising:
Calculate the cumulative of pixel line direction;
To line by line scan the cumulative value obtaining integral image of described image, each described pixel line direction of recursive calculation;
According to the scan value of described integral image, image configuration goes out integral image;
Calculated by the Haar feature of described integral image to described Haar classifier.
5. the method as described in claim 1-4 any one, is characterized in that, the described rgb value to described target location converts, and the colour switching obtaining described target location becomes the image of pre-set color, comprising:
The rgb value corresponding with pre-set color is transformed to the rgb value of data corresponding to the target location in the yuv data of the image of described generation, obtains the yuv data after converting;
According to the yuv data after described conversion, export the image of setting form.
6. a terminal, is characterized in that, comprising:
First recognition unit, for identify generation image in treat the target location of local discolouration;
Detecting unit, for detecting the rgb value of the target location identified;
First converter unit, for converting the rgb value of described target location, the colour switching obtaining described target location becomes the image of pre-set color.
7. terminal as claimed in claim 6, is characterized in that, described first recognition unit specifically for:
Application Haar classifier algorithm identifies described image, treats the target location of variable color described in acquisition.
8. terminal as claimed in claim 7, it is characterized in that, described first recognition unit comprises:
Haar classifier training unit, for apply AdaBoost Algorithm for Training sample Haar feature after obtain distinguishing the strong classifier of described target location and non-targeted position, all strong classifiers of screening cascade are Haar classifier;
Second recognition unit, the Haar feature for applying described Haar classifier carries out the identification of described target location;
Accelerate recognition unit, in identifying, utilize the calculating of integrogram algorithm to the Haar feature of described Haar classifier to accelerate.
9. terminal as claimed in claim 8, it is characterized in that, described acceleration recognition unit comprises:
First computing unit, for calculating the cumulative of pixel line direction;
Second computing unit, for described image of lining by line scan, the cumulative value obtaining integral image of each described pixel line direction of recursive calculation;
Integral image tectonic element, goes out integral image for image configuration according to the scan value of described integral image;
3rd computing unit, for calculating by the Haar feature of described integral image to described Haar classifier.
10. the terminal as described in claim 6-9 any one, is characterized in that, described first converter unit comprises:
Second converter unit, the rgb value for data corresponding to the target location in the yuv data of the image to described generation is transformed to the rgb value corresponding with pre-set color, obtains the yuv data after converting;
Output unit, for according to the yuv data after described conversion, exports the image of setting form.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510200800.2A CN104851114B (en) | 2015-04-24 | 2015-04-24 | A kind of method and terminal for realizing image local discoloration |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510200800.2A CN104851114B (en) | 2015-04-24 | 2015-04-24 | A kind of method and terminal for realizing image local discoloration |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104851114A true CN104851114A (en) | 2015-08-19 |
| CN104851114B CN104851114B (en) | 2018-05-01 |
Family
ID=53850741
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510200800.2A Expired - Fee Related CN104851114B (en) | 2015-04-24 | 2015-04-24 | A kind of method and terminal for realizing image local discoloration |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104851114B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105488819A (en) * | 2015-12-04 | 2016-04-13 | 小米科技有限责任公司 | Color template generation method and device and image processing method and device |
| CN106642003A (en) * | 2016-11-15 | 2017-05-10 | 广州视源电子科技股份有限公司 | Automatic color-changing method for jewelry and jewelry |
| CN109166162A (en) * | 2018-10-08 | 2019-01-08 | 苏州仙峰网络科技股份有限公司 | 2D color changing method based on fixed form and aspect |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1181569A (en) * | 1996-10-08 | 1998-05-13 | 夏普公司 | INformation processing apparatus |
| EP0852041A1 (en) * | 1995-09-14 | 1998-07-08 | Bently Mills, Inc. | Method and systems for manipulation of images of floor coverings or other fabrics |
| CN101043578A (en) * | 2006-03-21 | 2007-09-26 | 晨星半导体股份有限公司 | Hue regulation system and its regulation method |
| CN102567974A (en) * | 2010-12-16 | 2012-07-11 | 方正国际软件(北京)有限公司 | Method and system for adjusting local color of image |
| CN104519238A (en) * | 2013-09-26 | 2015-04-15 | 天津书生软件技术有限公司 | Color correction method |
-
2015
- 2015-04-24 CN CN201510200800.2A patent/CN104851114B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0852041A1 (en) * | 1995-09-14 | 1998-07-08 | Bently Mills, Inc. | Method and systems for manipulation of images of floor coverings or other fabrics |
| CN1181569A (en) * | 1996-10-08 | 1998-05-13 | 夏普公司 | INformation processing apparatus |
| CN101043578A (en) * | 2006-03-21 | 2007-09-26 | 晨星半导体股份有限公司 | Hue regulation system and its regulation method |
| CN102567974A (en) * | 2010-12-16 | 2012-07-11 | 方正国际软件(北京)有限公司 | Method and system for adjusting local color of image |
| CN104519238A (en) * | 2013-09-26 | 2015-04-15 | 天津书生软件技术有限公司 | Color correction method |
Non-Patent Citations (3)
| Title |
|---|
| 兰胜坤: "基于Adaboost算法的人脸检测分类器的设计与实现", 《电脑知识与技术》 * |
| 金立军 等: "基于类Haar特征与级联AdaBoost算法的防震锤识别", 《系统仿真学报》 * |
| 齐欣: "数码影像技术操作篇之六十三 图像色彩调整的基本方法(上)", 《照相机》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105488819A (en) * | 2015-12-04 | 2016-04-13 | 小米科技有限责任公司 | Color template generation method and device and image processing method and device |
| CN105488819B (en) * | 2015-12-04 | 2018-09-18 | 小米科技有限责任公司 | Generation method, image processing method and the device of color template |
| CN106642003A (en) * | 2016-11-15 | 2017-05-10 | 广州视源电子科技股份有限公司 | Automatic color-changing method for jewelry and jewelry |
| CN106642003B (en) * | 2016-11-15 | 2019-04-12 | 广州视源电子科技股份有限公司 | The method and jewellery of jewellery automatic color-changing |
| CN109166162A (en) * | 2018-10-08 | 2019-01-08 | 苏州仙峰网络科技股份有限公司 | 2D color changing method based on fixed form and aspect |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104851114B (en) | 2018-05-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR101970488B1 (en) | RGB-D Multi-layer Residual Feature Fusion Network for Indoor Semantic Segmentation | |
| CN107959851B (en) | Colour temperature detection method and device, computer readable storage medium and computer equipment | |
| US20160155241A1 (en) | Target Detection Method and Apparatus Based On Online Training | |
| CN105049718A (en) | Image processing method and terminal | |
| CN110263621B (en) | Image recognition method and device and readable storage medium | |
| MX2014004073A (en) | Device and method for automatically identifying a qr code. | |
| CN111385640B (en) | Video cover determining method, device, equipment and storage medium | |
| CN113792827B (en) | Target object recognition method, electronic device, and computer-readable storage medium | |
| CN112115979B (en) | Fusion method and device of infrared image and visible image | |
| CN113505768A (en) | Model training method, face recognition method, electronic device and storage medium | |
| CN106131441A (en) | Photographic method and device, electronic equipment | |
| CN103198311A (en) | Method and apparatus for recognizing a character based on a photographed image | |
| CN112052834A (en) | Face recognition method, device and equipment based on privacy protection | |
| CN104902182A (en) | Method and device for realizing continuous auto-focus | |
| CN105162520A (en) | Automatic identification method and information service system based on visible light illumination | |
| CN111163350B (en) | Image processing method, terminal and computer storage medium | |
| CN107808109B (en) | Two-dimensional code image identification method and mobile terminal | |
| CN104851114A (en) | Method for partial color changing of image, and terminal | |
| CN113079329A (en) | Matting method, related device and matting system | |
| CN107920205A (en) | Image processing method, device, storage medium and electronic equipment | |
| CN110365897A (en) | Image correcting method and device, electronic equipment, computer readable storage medium | |
| CN113610720A (en) | Video denoising method and device, computer readable medium and electronic device | |
| CN108416782A (en) | View-based access control model identifies and the tobacco leaf ranking method and system of illumination correction | |
| CN116630354B (en) | Video matting method, electronic device, storage medium and program product | |
| CN111080683B (en) | Image processing method, device, storage medium and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| EXSB | Decision made by sipo to initiate substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP01 | Change in the name or title of a patent holder |
Address after: Changan town in Guangdong province Dongguan 523860 usha Beach Road No. 18 Patentee after: GUANGDONG OPPO MOBILE TELECOMMUNICATIONS Corp.,Ltd. Address before: Changan town in Guangdong province Dongguan 523860 usha Beach Road No. 18 Patentee before: GUANGDONG OPPO MOBILE TELECOMMUNICATIONS Corp.,Ltd. |
|
| CP01 | Change in the name or title of a patent holder | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20180501 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |