CN105631391B - A kind of image processing method and system for realizing eyes amplification - Google Patents
A kind of image processing method and system for realizing eyes amplification Download PDFInfo
- Publication number
- CN105631391B CN105631391B CN201410617414.9A CN201410617414A CN105631391B CN 105631391 B CN105631391 B CN 105631391B CN 201410617414 A CN201410617414 A CN 201410617414A CN 105631391 B CN105631391 B CN 105631391B
- Authority
- CN
- China
- Prior art keywords
- pixel value
- ratio
- projection curve
- image
- curve
- 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.)
- Active
Links
Abstract
The present invention provides a kind of image processing method for realizing eyes amplification, comprising: is described according to the Gabor wavelet that the facial image of an input and Gabor wavelet establish face;Floor projection is carried out to the top half of the facial image and upright projection generates floor projection curve and upright projection curve;The floor projection curve and upright projection curve are normalized, floor projection curve and upright projection curve representation formula are established;The peak value of floor projection and upright projection is obtained according to the floor projection curve and upright projection curve representation formula, determines the coordinate of pupil in face;It is handled according to the coordinate pair eye areas every bit pixel of a pre-set radius and pupil, realizes eyes amplification.
Description
Technical field
The present invention relates to image procossing and mode identification technology, in particular at a kind of image for realizing eyes amplification
Manage method and system.
Background technique
In recent years, with the rapid development of smart phone, demand of the people to cell-phone function is more and more diversified.Wherein,
One important function of smart phone is self-timer.It can be applied to production head portrait, social networks using the photo that mobile phone is filmed
The numerous areas such as sharing.The U.S. face processing that self-timer image is realized on smart phone, is more emphasis concerned by people, wherein weighing
The U.S. face processing wanted just includes the processing of eyes, amplifies human eye by image procossing, so that everyone can possess a pair of fan
The oxeye of people.
Eyes enhanced processing belongs to a kind of bird caging of image, and existing processing technique is all by carrying out eye manually
The amplification of eyeball, generally require three parameters of manual setting: central point, paintbrush size and dynamics, this Series Manual are operated to use
It makes troubles at family.
Summary of the invention
The purpose of the present invention is to provide a kind of image processing methods and system for realizing eyes amplification, to solve existing skill
Art needs that the problem of making troubles to user is manually operated.
In order to solve the above technical problems, the present invention provides a kind of image processing method for realizing eyes amplification, feature exists
In, comprising:
It is described according to the Gabor wavelet that the facial image of an input and Gabor wavelet establish face;
Floor projection carried out to the top half of the facial image and upright projection generates floor projection curve and vertical
Drop shadow curve;
The floor projection curve and upright projection curve are normalized, floor projection curve and vertical is established
Drop shadow curve's expression formula;
The peak value of floor projection and upright projection is obtained according to the floor projection curve and upright projection curve representation formula,
Determine the coordinate of pupil in face;
It is handled according to the coordinate pair eye areas every bit pixel of a pre-set radius and pupil, realizes eyes amplification.
Further, in the image processing method for realizing eyes amplification, the face figure according to an input
The step of describing as the Gabor wavelet of establishing face with Gabor wavelet include:
Facial image and Gabor wavelet to input carry out convolution algorithm, and improve convolution speed using Fourier transformation;
Image Gabor wavelet transformation in different center frequency and different directions is normalized.
Further, in the described image processing method for realizing eyes amplification, the facial image of described pair of input with
Gabor wavelet carries out convolution algorithm and is completed by following formula:Wherein, G
(x, y) is the facial image of input, and Θ indicates convolution algorithm,Corresponding to radial center frequency be X0, direction is
The wavelet convolution result of H.
Further, in the described image processing method for realizing eyes amplification, it is described by different center frequency and not
Image Gabor wavelet transformation on equidirectional is normalized to be completed by following formula:Wherein, n is the centre frequency number selected, and m is the side selected
To number, C becomes the Gabor characteristic vector of image.
Further, in the described image processing method for realizing eyes amplification, the floor projection curve and vertical
Drop shadow curve's expression formula are as follows:
Wherein, H (x) is floor projection curve, and V (y) is upright projection curve, and G (x, y) is the facial image of input.
Further, described according to a pre-set radius and pupil in the image processing method for realizing eyes amplification
The step of coordinate pair eye areas every bit pixel in hole is handled include:
By pupil coordinate C1 (X1, Y1), C2 (X2, Y2) and pre-set radius R, every bit pixel A 1 in pair radius (x1,
Y1 it) is handled with A2 (x2, y2);
The ratio of the distance between A1 and C1 and R are calculated, reduced value size carries out judging laggard row pixel value replacement;
The ratio of the distance between A2 and C2 and R are calculated, reduced value size carries out judging laggard row pixel value replacement.
Further, in the described image processing method for realizing eyes amplification, it is described calculate between A1 and C1 away from
From the ratio with R, reduced value size carries out judging that the step of laggard row pixel value is replaced includes:
If ratio is greater than 1, its pixel value is changed to the pixel value of point A ' (x1 ', y1 ') into, the position of A ' passes through following public affairs
Formula obtains:
If its pixel value less than 1, is changed into the pixel value of point A ' (x1 ', y1 '), the position of A ' passes through following public affairs by ratio
Formula obtains:
If ratio is equal to 1, its pixel value is constant.
Further, in the described image processing method for realizing eyes amplification, it is described calculate between A2 and C2 away from
From the ratio with R, reduced value size carries out judging that the step of laggard row pixel value is replaced includes:
If ratio is greater than 1 into, its pixel value is changed to the pixel value of point A2 ' (x2 ', y2 '), the position of A2 ' passes through following
Formula obtains:
If its pixel value less than 1, is changed into the pixel value of point A2 ' (x1 ', y1 ') by ratio, the position of A2 ' passes through following
Formula obtains:
If ratio is equal to 1, its pixel value is constant.
Correspondingly, the present invention also provides a kind of image processing systems for realizing eyes amplification, comprising:
Gabor wavelet describing module establishes the Gabor of face for the facial image and Gabor wavelet according to an input
Small echo description;
Projection module carries out floor projection for the top half to the facial image and upright projection generates horizontal throw
Shadow curve and upright projection curve;
Curve representation formula generation module, for place to be normalized to the floor projection curve and upright projection curve
Reason, establishes floor projection curve and upright projection curve representation formula;
Pupil coordinate generation module, for obtaining level according to the floor projection curve and upright projection curve representation formula
The peak value of projection and upright projection, determines the coordinate of pupil in face;
Processes pixel module, at the coordinate pair eye areas every bit pixel according to a pre-set radius and pupil
Reason realizes eyes amplification.
Further, in the image processing system for realizing eyes amplification, the Gabor wavelet describing module packet
It includes:
Convolution algorithm module for the facial image and Gabor wavelet progress convolution algorithm to input, and uses Fourier
Transformation improves convolution speed;
Normalized module is carried out for converting the image Gabor wavelet in different center frequency and different directions
Normalized.
Further, right in the convolution algorithm module in the image processing system for realizing eyes amplification
The facial image and Gabor wavelet of input carry out convolution algorithm and are completed by following formula:Wherein, G (x, y) is the facial image of input, and Θ indicates convolution algorithm,Corresponding to the wavelet convolution result that radial center frequency is X0, direction is H.
Further, in the image processing system for realizing eyes amplification, in the normalized module,
Image Gabor wavelet transformation in different center frequency and different directions is normalized and is completed by following formula:Wherein, n is the centre frequency number selected, and m is the side selected
To number, C becomes the Gabor characteristic vector of image.
Further, in the image processing system for realizing eyes amplification, mould is generated in the curve representation formula
In block, floor projection curve and upright projection curve representation formula are as follows:
Wherein, H (x) is floor projection curve, and V (y) is upright projection curve, and G (x, y) is the facial image of input.
Further, in the image processing system for realizing eyes amplification, the processes pixel module includes:
Processing module, it is every in pair radius for passing through pupil coordinate C1 (X1, Y1), C2 (X2, Y2) and pre-set radius R
Some pixel As 1 (x1, y1) and A2 (x2, y2) are handled;
First computing module, for calculating the ratio of the distance between A1 and C1 with R, reduced value size judge laggard
Row pixel value replacement;
Second computing module, for calculating the ratio of the distance between A2 and C2 with R, reduced value size judge laggard
Row pixel value replacement.
Further, in the image processing system for realizing eyes amplification, in first computing module:
If ratio is greater than 1, its pixel value is changed to the pixel value of point A ' (x1 ', y1 ') into, the position of A ' passes through following public affairs
Formula obtains:
If its pixel value less than 1, is changed into the pixel value of point A ' (x1 ', y1 '), the position of A ' passes through following public affairs by ratio
Formula obtains:
If ratio is equal to 1, its pixel value is constant.
Further, in the image processing system for realizing eyes amplification, in second computing module:
If ratio is greater than 1 into, its pixel value is changed to the pixel value of point A2 ' (x2 ', y2 '), the position of A2 ' passes through following
Formula obtains:
If its pixel value less than 1, is changed into the pixel value of point A2 ' (x1 ', y1 ') by ratio, the position of A2 ' passes through following
Formula obtains:
If ratio is equal to 1, its pixel value is constant.
The image processing method and system provided by the invention for realizing eyes amplification, has the advantages that and passes through
Gabor wavelet models face characteristic, calculates the floor projection and upright projection of facial image top half, thus
To the accurate coordinates of human eye, human eye area every bit pixel is handled, from eyeball get over into those of pixel variation it is smaller,
And remoter transformation is bigger, to realize that human eye equal proportion is amplified, and guarantees that amplification effect is natural, true.
Detailed description of the invention
Fig. 1 is the flow chart of the image processing method for realizing eyes amplification of the embodiment of the present invention;
Fig. 2 is that the distance between pixel A 1 and pupil coordinate C1 of the embodiment of the present invention and the ratio of pre-set radius R are greater than 1
When schematic diagram;
Fig. 3 is the distance between pixel A 1 and pupil coordinate C1 of the embodiment of the present invention with the ratio of pre-set radius R less than 1
When schematic diagram;
Fig. 4 is that the distance between pixel A 1 and pupil coordinate C1 of the embodiment of the present invention and the ratio of pre-set radius R are equal to 1
When schematic diagram;
Fig. 5 is that the distance between pixel A 2 and pupil coordinate C2 of the embodiment of the present invention and the ratio of pre-set radius R are greater than 1
When schematic diagram;
Fig. 6 is the distance between pixel A 2 and pupil coordinate C2 of the embodiment of the present invention with the ratio of pre-set radius R less than 1
When schematic diagram;
Fig. 7 is that the distance between pixel A 2 and pupil coordinate C2 of the embodiment of the present invention and the ratio of pre-set radius R are equal to 1
When schematic diagram.
Specific embodiment
To the image processing method of realization eyes amplification proposed by the present invention and it is below in conjunction with the drawings and specific embodiments
System is described in further detail.According to following explanation and claims, advantages and features of the invention will be become apparent from.It needs to illustrate
, attached drawing is all made of very simplified form and using non-accurate ratio, only conveniently, lucidly to aid in illustrating originally
The purpose of inventive embodiments.
Referring to FIG. 1, it is the flow chart of the image processing method for realizing eyes amplification of the embodiment of the present invention.Such as Fig. 1
It is shown, the present invention provide it is a kind of realize eyes amplification image processing method include:
Step 1: it is described according to the Gabor wavelet that the facial image of an input and Gabor wavelet establish face;
Specifically, convolution algorithm first is carried out to the facial image of input and Gabor wavelet, it may be assumed thatWherein, G (x, y) is the facial image of input, and Θ indicates convolution algorithm,Corresponding to the wavelet convolution result that radial center frequency is X0, direction is H.Then it is mentioned using Fourier transformation
Finally the image Gabor wavelet transformation in different center frequency and different directions is normalized for high convolution speed,
That is:Wherein, n is the centre frequency number selected, and m is to select
Direction number, C become the Gabor characteristic vector of image.It, can since Gabor wavelet has stronger response in image edge
To utilize the characteristic, the Gabor wavelet description of face is established.
Step 2: floor projection is carried out to the top half of the facial image and upright projection generates floor projection curve
With upright projection curve;
Step 3: being normalized the floor projection curve and upright projection curve, establishes floor projection song
Line and upright projection curve representation formula, in the floor projection H (x) in the region image [y1, y2] and the upright projection in the region [x1, x2]
V (y) is indicated are as follows:
Wherein, H (x) is floor projection curve, and V (y) is upright projection curve, and G (x, y) is the facial image of input.
Step 4: floor projection and upright projection are obtained according to the floor projection curve and upright projection curve representation formula
Peak value, determine the X of pupil in face, Y-coordinate;
Step 5: being handled according to the coordinate pair eye areas every bit pixel of a pre-set radius R and pupil, realizes eye
Eyeball amplification.
Pass through pupil coordinate C1 (X1, Y1), C2 (X2, Y2) and pre-set radius R, the every bit pixel A 1 in pair radius first
(x1, y1) and A2 (x2, y2) are handled;
Then, the ratio of the distance between A1 and C1 and R are calculated, reduced value size carries out judging that laggard row pixel value is replaced
It changes;
Specifically, as shown in Fig. 2,
If ratio is greater than 1 into, its pixel value is changed to the pixel value of point A1 ' (x1 ', y1 '), the position of A1 ' passes through following
Formula obtains:
As shown in figure 3, if its pixel value less than 1, is changed into the pixel value of point A1 ' (x1 ', y1 '), the position of A1 ' by ratio
It sets and is obtained by following formula:
As shown in figure 4, if ratio be equal to 1, its pixel value is constant.
Finally, calculating the ratio of the distance between A2 and C2 and R, reduced value size carries out judging that laggard row pixel value is replaced
It changes.
Specifically, as shown in figure 5,
If ratio is greater than 1 into, its pixel value is changed to the pixel value of point A2 ' (x2 ', y2 '), the position of A2 ' passes through following
Formula obtains:
As shown in fig. 6, if its pixel value less than 1, is changed into the pixel value of point A2 ' (x1 ', y1 '), the position of A2 ' by ratio
It sets and is obtained by following formula:
As shown in fig. 7, if ratio be equal to 1, its pixel value is constant.
Correspondingly, the present invention also provides a kind of image processing systems for realizing eyes amplification, comprising: Gabor wavelet description
Module, projection module, curve representation formula generation module, pupil coordinate generation module and processes pixel module;
The Gabor wavelet describing module, for establishing face according to the facial image and Gabor wavelet of an input
Gabor wavelet description;
Further, the Gabor wavelet describing module further include:
Convolution algorithm module, for the facial image and Gabor wavelet progress convolution algorithm to input, it may be assumed thatWherein, G (x, y) is the facial image of input, and Θ indicates convolution algorithm,Corresponding to the wavelet convolution that radial center frequency is X0, direction is H as a result, and being improved using Fourier transformation
Convolution speed;
Normalized module is carried out for converting the image Gabor wavelet in different center frequency and different directions
Normalized, it may be assumed thatWherein, n is the centre frequency selected
Number, m are the direction number selected, and C becomes the Gabor characteristic vector of image.
The projection module carries out floor projection for the top half to the facial image and upright projection generates water
Flat drop shadow curve and upright projection curve;
The curve representation formula generation module, for the floor projection curve and upright projection curve to be normalized
Processing, establishes floor projection curve and upright projection curve representation formula;The region image [y1, y2] floor projection H (x) and
The upright projection V (y) in the region [x1, x2] is indicated are as follows:
Wherein, H (x) is floor projection curve, and V (y) is upright projection curve, and G (x, y) is the facial image of input.
The pupil coordinate generation module, for being obtained according to the floor projection curve and upright projection curve representation formula
The peak value of floor projection and upright projection determines the coordinate of pupil in face;
The processes pixel module, for according to the coordinate pair eye areas every bit pixel of a pre-set radius and pupil into
Eyes amplification is realized in row processing.
Further, the processes pixel module includes:
Processing module, it is every in pair radius for passing through pupil coordinate C1 (X1, Y1), C2 (X2, Y2) and pre-set radius R
Some pixel As 1 (x1, y1) and A2 (x2, y2) are handled;
First computing module, for calculating the ratio of the distance between A1 and C1 with R, reduced value size judge laggard
Row pixel value replacement;
Specifically, if ratio is greater than 1 into its pixel value to be changed to the pixel value of point A1 ' (x1 ', y1 '), the position of A1 ' is logical
Cross following formula acquisition:
If its pixel value less than 1, is changed into the pixel value of point A1 ' (x1 ', y1 ') by ratio, the position of A1 ' passes through following
Formula obtains:
If ratio is equal to 1, its pixel value is constant.
Second computing module, for calculating the ratio of the distance between A2 and C2 with R, reduced value size judge laggard
Row pixel value replacement.
Specifically, if ratio is greater than 1 into its pixel value to be changed to the pixel value of point A2 ' (x2 ', y2 '), the position of A2 ' is logical
Cross following formula acquisition:
If its pixel value less than 1, is changed into the pixel value of point A2 ' (x1 ', y1 ') by ratio, the position of A2 ' passes through following
Formula obtains:
If ratio is equal to 1, its pixel value is constant.
In conclusion the present invention models face characteristic by Gabor wavelet, facial image top half is calculated
Floor projection and upright projection human eye area every bit pixel is handled, to obtain the accurate coordinates of human eye from eye
Pearl get over into those of pixel variation it is smaller, and remoter transformation is bigger, to realize that human eye equal proportion is amplified, and guarantees amplification
Effect is natural, true.
Foregoing description is only the description to present pre-ferred embodiments, not to any restriction of the scope of the invention, this hair
Any change, the modification that the those of ordinary skill in bright field does according to the disclosure above content, belong to the protection of claims
Range.
Claims (10)
1. a kind of image processing method for realizing eyes amplification characterized by comprising
It is described according to the Gabor wavelet that the facial image of an input and Gabor wavelet establish face;
Floor projection is carried out to the top half of the facial image and upright projection generates floor projection curve and upright projection
Curve;
The floor projection curve and upright projection curve are normalized, floor projection curve and upright projection are established
Curve representation formula;
The peak value of floor projection and upright projection is obtained according to the floor projection curve and upright projection curve representation formula, is determined
The coordinate of pupil in face;
It is handled according to the coordinate pair eye areas every bit pixel of a pre-set radius and pupil, realizes eyes amplification;
Wherein, the step of coordinate pair eye areas every bit pixel according to a pre-set radius and pupil is handled packet
It includes:
Every bit pixel A 1 (x1, y1) by pupil coordinate C1 (X1, Y1), C2 (X2, Y2) and pre-set radius R, in pair radius
It is handled with A2 (x2, y2);
The first ratio of the distance between A1 and C1 and R are calculated, if first ratio is greater than 1, its pixel value is changed into a little
The pixel value of A ' (x1 ', y1 '), the position of A ' pass through following formula and obtain:
If its pixel value less than 1, is changed into the pixel value of point A ' (x1 ', y1 ') by first ratio, the position of A ' by with
Lower formula obtains:
If first ratio is equal to 1, its pixel value is constant;
The second ratio of the distance between A2 and C2 and R are calculated, if second ratio is greater than 1, its pixel value is changed into a little
The pixel value of A2 ' (x2 ', y2 '), the position of A2 ' pass through following formula and obtain:
If its pixel value less than 1, is changed into the pixel value of point A2 ' (x1 ', y1 '), the position of A2 ' passes through by second ratio
Following formula obtains:
If second ratio is equal to 1, its pixel value is constant.
2. as described in claim 1 realize eyes amplification image processing method, which is characterized in that it is described according to one input
The step of Gabor wavelet that facial image establishes face with Gabor wavelet describes include:
Facial image and Gabor wavelet to input carry out convolution algorithm, and improve convolution speed using Fourier transformation;
Image Gabor wavelet transformation in different center frequency and different directions is normalized.
3. realizing the image processing method of eyes amplification as claimed in claim 2, which is characterized in that the face of described pair of input
Image and Gabor wavelet carry out convolution algorithm and are completed by following formula:
Wherein, G (x, y) is the facial image of input, and Θ indicates convolution algorithm,Be X0 corresponding to radial center frequency,
Direction is the wavelet convolution result of H.
4. realizing the image processing method of eyes amplification as claimed in claim 2, which is characterized in that described by different center frequencies
Image Gabor wavelet transformation in rate and different directions is normalized to be completed by following formula:Wherein, n is the centre frequency number selected, and m is the side selected
To number, C becomes the Gabor characteristic vector of image.
5. realizing the image processing method of eyes amplification as described in claim 1, which is characterized in that the floor projection curve
With upright projection curve representation formula are as follows:
Wherein, H (x) is floor projection curve, and V (y) is upright projection curve, and G (x, y) is the facial image of input.
6. a kind of image processing system for realizing eyes amplification characterized by comprising
Gabor wavelet describing module establishes the Gabor wavelet of face for the facial image and Gabor wavelet according to an input
Description;
Projection module carries out floor projection for the top half to the facial image and upright projection generates floor projection song
Line and upright projection curve;
Curve representation formula generation module is built for the floor projection curve and upright projection curve to be normalized
Vertical floor projection curve and upright projection curve representation formula;
Pupil coordinate generation module, for obtaining floor projection according to the floor projection curve and upright projection curve representation formula
With the peak value of upright projection, the coordinate of pupil in face is determined;
Processes pixel module, for being handled according to the coordinate pair eye areas every bit pixel of a pre-set radius and pupil,
Realize eyes amplification;
Wherein, the processes pixel module includes:
Processing module, the every bit for passing through pupil coordinate C1 (X1, Y1), C2 (X2, Y2) and pre-set radius R, in pair radius
Pixel A 1 (x1, y1) and A2 (x2, y2) are handled;
First computing module, for calculating the first ratio of the distance between A1 and C1 with R, if first ratio is greater than 1,
Its pixel value is changed to the pixel value of point A ' (x1 ', y1 ') into, the position of A ' passes through following formula and obtains:
If its pixel value less than 1, is changed into the pixel value of point A ' (x1 ', y1 ') by first ratio, the position of A ' by with
Lower formula obtains:
If first ratio is equal to 1, its pixel value is constant;
Second computing module, for calculating the second ratio of the distance between A2 and C2 with R, if second ratio is greater than 1,
Its pixel value is changed to the pixel value of point A2 ' (x2 ', y2 ') into, the position of A2 ' passes through following formula and obtains:
If its pixel value less than 1, is changed into the pixel value of point A2 ' (x1 ', y1 '), the position of A2 ' passes through by second ratio
Following formula obtains:
If second ratio is equal to 1, its pixel value is constant.
7. realizing the image processing system of eyes amplification as claimed in claim 6, which is characterized in that the Gabor wavelet is retouched
Stating module includes:
Convolution algorithm module for the facial image and Gabor wavelet progress convolution algorithm to input, and uses Fourier transformation
Improve convolution speed;
Normalized module, for the image Gabor wavelet transformation in different center frequency and different directions to be carried out normalizing
Change processing.
8. realizing the image processing system of eyes amplification as claimed in claim 7, which is characterized in that in the convolution algorithm mould
In block, facial image and Gabor wavelet to input carry out convolution algorithm and are completed by following formula:Wherein, G (x, y) is the facial image of input, and Θ indicates convolution algorithm,Corresponding to the wavelet convolution result that radial center frequency is X0, direction is H.
9. realizing the image processing system of eyes amplification as claimed in claim 7, which is characterized in that in the normalized
In module, the image Gabor wavelet transformation in different center frequency and different directions is normalized through following public affairs
Formula is completed:Wherein, n is the centre frequency number selected, and m is choosing
Direction number, C become the Gabor characteristic vector of image.
10. realizing the image processing system of eyes amplification as claimed in claim 6, which is characterized in that in the curve representation
In formula generation module, floor projection curve and upright projection curve representation formula are as follows:
Wherein, H (x) is floor projection curve, and V (y) is upright projection curve, and G (x, y) is the facial image of input.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410617414.9A CN105631391B (en) | 2014-11-05 | 2014-11-05 | A kind of image processing method and system for realizing eyes amplification |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410617414.9A CN105631391B (en) | 2014-11-05 | 2014-11-05 | A kind of image processing method and system for realizing eyes amplification |
Publications (2)
Publication Number | Publication Date |
---|---|
CN105631391A CN105631391A (en) | 2016-06-01 |
CN105631391B true CN105631391B (en) | 2019-03-22 |
Family
ID=56046308
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201410617414.9A Active CN105631391B (en) | 2014-11-05 | 2014-11-05 | A kind of image processing method and system for realizing eyes amplification |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN105631391B (en) |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109886107A (en) * | 2019-01-15 | 2019-06-14 | 北京奇艺世纪科技有限公司 | Eyes image processing method, equipment, image processing equipment, medium |
CN111784604B (en) * | 2020-06-29 | 2022-02-18 | 北京字节跳动网络技术有限公司 | Image processing method, device, equipment and computer readable storage medium |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7634109B2 (en) * | 2003-06-26 | 2009-12-15 | Fotonation Ireland Limited | Digital image processing using face detection information |
CN102360421A (en) * | 2011-10-19 | 2012-02-22 | 苏州大学 | Face identification method and system based on video streaming |
CN102426652A (en) * | 2011-10-10 | 2012-04-25 | 北京工业大学 | Traditional Chinese medicine face color identifying and retrieving method based on image analysis |
CN103488990A (en) * | 2013-09-29 | 2014-01-01 | 武汉虹识技术有限公司 | Method and device for extracting eyelash image and locating pupil through cross neighborhood method |
-
2014
- 2014-11-05 CN CN201410617414.9A patent/CN105631391B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7634109B2 (en) * | 2003-06-26 | 2009-12-15 | Fotonation Ireland Limited | Digital image processing using face detection information |
CN102426652A (en) * | 2011-10-10 | 2012-04-25 | 北京工业大学 | Traditional Chinese medicine face color identifying and retrieving method based on image analysis |
CN102360421A (en) * | 2011-10-19 | 2012-02-22 | 苏州大学 | Face identification method and system based on video streaming |
CN103488990A (en) * | 2013-09-29 | 2014-01-01 | 武汉虹识技术有限公司 | Method and device for extracting eyelash image and locating pupil through cross neighborhood method |
Non-Patent Citations (2)
Title |
---|
图像美容之眼睛放大算法;laviewpbt;《http://www.cnblogs.com/Imageshop/p/3847357.html》;20140715;1-5 |
基于Gabor变换的人眼定位方法;李嵩 等;《测控技术》;20060531;第25卷(第5期);27-29,32 |
Also Published As
Publication number | Publication date |
---|---|
CN105631391A (en) | 2016-06-01 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US11410284B2 (en) | Face beautification method and apparatus, computer device, and storage medium | |
CN105374055A (en) | Image processing method and device | |
CN109359575A (en) | Method for detecting human face, method for processing business, device, terminal and medium | |
CN103793719A (en) | Monocular distance-measuring method and system based on human eye positioning | |
CN103632672B (en) | Voice-changing system, voice-changing method, man-machine interaction system and man-machine interaction method | |
CN103218605B (en) | A kind of fast human-eye positioning method based on integral projection and rim detection | |
CN110991266B (en) | Binocular face living body detection method and device | |
CN105046246A (en) | Identification photo camera capable of performing human image posture photography prompting and human image posture detection method | |
CN102147857A (en) | Image processing method for detecting similar round by using improved hough transformation | |
CN108491809A (en) | The method and apparatus for generating model for generating near-infrared image | |
CN106920211A (en) | U.S. face processing method, device and terminal device | |
CN108363995A (en) | Method and apparatus for generating data | |
CN105704390A (en) | Photo-modifying photo-shooting method and device and mobile terminal | |
CN108549853B (en) | Image processing method, mobile terminal and computer readable storage medium | |
US20230065433A1 (en) | Image processing method and apparatus, electronic device, and storage medium | |
CN108984481A (en) | A kind of homography matrix estimation method based on convolutional neural networks | |
CN102262536A (en) | window interface processing method and device | |
Hu et al. | Face illumination recovery for the deep learning feature under severe illumination variations | |
CN105631391B (en) | A kind of image processing method and system for realizing eyes amplification | |
CN106778574A (en) | For the detection method and device of facial image | |
CN107194310A (en) | The rigid-object tracking matched based on scene change classifications and online local feature | |
CN109241822A (en) | A kind of multi-faceted method for detecting human face and system based on MTCNN | |
CN109669537B (en) | A kind of man-machine interactive system based on computer virtual interface | |
CN104156689B (en) | Method and device for positioning feature information of target object | |
CN110070143A (en) | Obtain method, apparatus, equipment and the storage medium of training data |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20160601 Assignee: Shanghai Li Ke Semiconductor Technology Co., Ltd. Assignor: Leadcore Technology Co., Ltd. Contract record no.: 2018990000159 Denomination of invention: Image processing method and system for achieving eye magnification License type: Common License Record date: 20180615 |
|
EE01 | Entry into force of recordation of patent licensing contract | ||
GR01 | Patent grant | ||
GR01 | Patent grant |