CN105205779B - A kind of eyes image processing method, system and camera terminal based on anamorphose - Google Patents
A kind of eyes image processing method, system and camera terminal based on anamorphose Download PDFInfo
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- CN105205779B CN105205779B CN201510584787.5A CN201510584787A CN105205779B CN 105205779 B CN105205779 B CN 105205779B CN 201510584787 A CN201510584787 A CN 201510584787A CN 105205779 B CN105205779 B CN 105205779B
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- 238000003672 processing method Methods 0.000 title claims abstract description 15
- 238000009792 diffusion process Methods 0.000 claims abstract description 67
- 230000000694 effects Effects 0.000 claims abstract description 30
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 19
- 230000003321 amplification Effects 0.000 claims abstract description 10
- 238000003199 nucleic acid amplification method Methods 0.000 claims abstract description 10
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 5
- 238000000205 computational method Methods 0.000 claims description 3
- 210000000746 body region Anatomy 0.000 claims 1
- 238000000034 method Methods 0.000 description 28
- 238000000513 principal component analysis Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000001815 facial effect Effects 0.000 description 3
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- 238000004458 analytical method Methods 0.000 description 2
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- G06T3/04—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/193—Preprocessing; Feature extraction
Abstract
The invention discloses a kind of eyes image processing method, system and camera terminal based on anamorphose, it to pending image by carrying out recognition of face, obtain face area characteristic point, and extract ocular characteristic point from the face area characteristic point, then the calculating to external diffusion is carried out according to preset diffusion ratio to the ocular characteristic point, the processing for carrying out the anamorphose algorithm of feature based point to the pending image according to the position of the ocular characteristic point before diffusion and after diffusion, obtains the effect image of ocular amplification；The present invention accuracy rate higher that not only ocular deforms, image fault rate is lower, and overall effect is more preferable, and algorithm space complexity and time complexity are low, the value with higher engineer application.
Description
Technical field
The present invention relates to technical field of image processing, especially a kind of eyes image processing method based on anamorphose and
Its system using this method, camera terminal.
Background technology
Continuous universal with portable equipment, camera also becomes its basic configuration, and the function of its hardware and software also with
It is abundant, medium-term and long-term be concerned and perfect function is exactly self-timer.This demand has greatly played the ability of portable equipment,
Anywhere, user can be made to take a photograph, to life, social activity and work all brings great convenience and temperament and interest.
In the demand of Self-timer, the processing of eye effect, especially beautification are even more emphasis of people's attention.Not merely
It is for the considerations of liking to be beautiful, everyone, which is intended to oneself, can possess the eyes of more attractive.Many times because of shooting
Environment, effect, opportunity are barely satisfactory, and the effect for allowing for eyes is unable to reach requirement, and such case just needs the figure to shooting
As its eyes is handled.Existing common method, be by the Digital Image Processing after shooting come to eyes into
Row improves, and this mode is most simple and direct, it can be readily appreciated that not only simple but also safe and reliable.Then, it one is asked to solve this
Topic, current mode are handled eyes in the later stage of digital imagery output by means of digital image editing software.But
It is that not all people can properly use image editing software, especially eye to handle in actual conditions, more not only
It is that the function of software itself causes inconvenience, it is contemplated that the complexity of eyes image pixel, personal Aesthetic Basis, operation are ripe
Practicing degree can all cause to be difficult to get started and grasp, and then, for the processing of eye, traditional mode is complicated for operation, threshold is high, and
And edit session is long, it is difficult to hold, effect is unstable, is easy to cause image fault.
Invention content
The present invention to solve the above problems, provide a kind of eyes image processing method based on anamorphose, system and
Camera terminal, accuracy rate higher, image fault rate is lower, and overall effect is more preferable.
To achieve the above object, the technical solution adopted by the present invention is：
First, the present invention provides a kind of eyes image processing method based on anamorphose comprising following steps：
10. a pair pending image carries out recognition of face, face area characteristic point is obtained；
20. extracting ocular characteristic point from the face area characteristic point；
30. the ocular characteristic point described in pair carries out the calculating to external diffusion according to preset diffusion ratio；
40. being based on to the pending image according to the position of the ocular characteristic point before diffusion and after diffusion
The processing of the anamorphose algorithm of characteristic point obtains the effect image of ocular amplification.
Preferably, face area characteristic point is obtained in the step 10, refers to obtaining the face adjacent with ocular
The characteristic point in region or the characteristic point of face's overall region.
Preferably, the ocular characteristic point in the step 20, including the left eye angle point of left eye region, right eye angle
Point, superior orbit vertex, inferior orbit vertex and/or the left eye angle point of right eye region, right eye angle point, superior orbit vertex, inferior orbit top
Point.
Preferably, the ocular characteristic point is carried out outward according to preset diffusion ratio in the step 30
The calculating of diffusion, calculation formula are as follows：
New Points=Old Points+ (Old Points+Center Points) * t%；
Wherein, New Points refer to the coordinate value of the left eye region characteristic point or right eye region characteristic point after diffusion,
Old Points refer to the coordinate value of the corresponding left eye region characteristic point or right eye region characteristic point before diffusion, Center
Points refers to the coordinate value of left eye central point or right eye central point, and t% refers to diffusion ratio.
Preferably, the computational methods of the coordinate value of the left eye central point or right eye central point are as follows：
Center Points=Sum (Old Points)/Num；
Wherein, Sum (Old Points) refers to the seat of the left eye region characteristic point or right eye region characteristic point before diffusion
The sum of scale value, Num are the quantity of corresponding left eye region characteristic point or right eye region characteristic point, and Center Points are meter
The coordinate value of obtained left eye central point or right eye central point.
Preferably, in the step 40 according to diffusion before and diffusion after ocular characteristic point position to described
The processing that pending image carries out the anamorphose algorithm of feature based point obtains the effect image of ocular amplification, further
Include the following steps：
41. calculating all facial regions of pending image according to the position of the ocular characteristic point before diffusion and after diffusion
Motion-vector dx and dy of the characteristic of field point in horizontal and vertical both direction.
42. calculating the color of each pixel of effect image according to the motion-vector of the face area characteristic point
Value.
Preferably, the anamorphose algorithm of feature based point is carried out to the pending image in the step 40
After processing, processing further also is sharpened to deformed image.
Secondly, the eyes image processing system based on anamorphose that the present invention also provides a kind of comprising：
Face recognition module obtains face area characteristic point for carrying out recognition of face to pending image；
Ocular feature point extraction module, for extracting ocular feature from the face area characteristic point
Point；
Computing module is spread, for being carried out to external diffusion according to preset diffusion ratio to the ocular characteristic point
Calculating；
Warped processing module, for waiting locating to described according to the position of the ocular characteristic point before diffusion and after diffusion
The processing that image carries out the anamorphose algorithm of feature based point is managed, the effect image of ocular amplification is obtained.
Preferably, further include Edge contrast module, for being sharpened processing to deformed image.
In addition, the present invention also provides a kind of camera terminals, which is characterized in that the camera terminal includes being based on as described above
The eyes image processing system of anamorphose.
Preferably, the camera terminal includes：Mobile phone, digital camera or tablet computer.
The beneficial effects of the invention are as follows：
A kind of eyes image processing method, system and the camera terminal based on anamorphose of the present invention, by treating
It handles image and carries out recognition of face, obtain face area characteristic point, and eye is extracted from the face area characteristic point
Then provincial characteristics point carries out the calculating to external diffusion, root to the ocular characteristic point according to preset diffusion ratio
The image of feature based point is carried out to the pending image according to the position of the ocular characteristic point before diffusion and after diffusion
The processing of deformation algorithm obtains the effect image of ocular amplification；The present invention accuracy rate higher that not only ocular deforms,
Image fault rate is lower, and overall effect is more preferable, and algorithm space complexity and time complexity are low, and there is higher engineering to answer
Value.
Description of the drawings
Attached drawing described herein is used to provide further understanding of the present invention, and constitutes the part of the present invention, this hair
Bright illustrative embodiments and their description are not constituted improper limitations of the present invention for explaining the present invention.In the accompanying drawings：
Fig. 1 is that the present invention is based on the general flow charts of the eyes image processing method of anamorphose；
Fig. 2 is that the present invention is based on the structural schematic diagrams of the eyes image processing system of anamorphose；
Fig. 3 is the structural schematic diagram of camera terminal of the present invention；
Fig. 4 is the extraction schematic diagram of ocular characteristic point.
Specific implementation mode
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.It should be appreciated that specific embodiment described herein is only solving
The present invention is released, is not intended to limit the present invention.Based on the embodiments of the present invention, those of ordinary skill in the art are not making
The every other embodiment obtained under the premise of creative work, shall fall within the protection scope of the present invention.
As shown in Figure 1, a kind of eyes image processing method based on anamorphose of the present invention comprising following steps：
10. a pair pending image carries out recognition of face, face area characteristic point is obtained；
20. extracting ocular characteristic point from the face area characteristic point；
30. the ocular characteristic point described in pair carries out the calculating to external diffusion according to preset diffusion ratio；
40. being based on to the pending image according to the position of the ocular characteristic point before diffusion and after diffusion
The processing of the anamorphose algorithm of characteristic point obtains the effect image of ocular amplification.
Recognition of face is carried out to pending image in the step 10, which can use following algorithm：
1. the method based on template matches:Template is divided into two dimension pattern plate and three-dimensional template, core concept:Utilize the face of people
Characteristic rule establishes an adjustable model framework of solid, is positioned and is adjusted with model framework after the face location for orienting people
The face feature position of people solves the viewing angle in face recognition process, blocks and the influence of the factors such as expression shape change.
2. being based on singular value features method：The singular value features of facial image matrix reflect the essential attribute of image, can
To be utilized to carry out Classification and Identification.
3. sub-space analysis method：Because it has the characteristics that descriptive strong, good, the quilt that calculates small cost, easy realization and separability
It is widely used in face characteristic extraction, becomes one of the main stream approach of current face's identification.
4. locality preserving projections (Locality Preserving Projections, LPP) are a kind of new subspaces point
Analysis method, it is the linear approximation of nonlinear method Laplacian Eigen map, has both solved the conventional linears method such as PCA
The shortcomings that being difficult to keep initial data non-linearity manifold, and solve nonlinear method and be difficult to obtain new sample point low dimension projective
Disadvantage.
5. principal component analysis (PCA)：A kind of important method of PCA area of pattern recognition, has been widely used in face
In recognizer, a significant obstacle is faced with based on PCA face identification systems in the application：Incremental learning problem.Increment PCA
Algorithm reconstructs mostly important PCS by newly-increased sample, but this method is with the increase of sample, needs constantly to give up some inessential
PC, to maintain subspace dimension constant, thus this method precision is slightly worse.
6. other methods：Elastic Matching method, eigenfaces (being converted based on KL), artificial neural network method, supporting vector
Machine method is based on integral image characteristic method (adaboost study), is based on probabilistic model method.
Face area characteristic point is obtained in the step 10, refers to the spy for obtaining the face area adjacent with ocular
The characteristic point of sign point or face's overall region.In the present embodiment, by above-mentioned face recognition algorithms, face area is obtained
106 characteristic points.
Ocular characteristic point in the step 20, including the left eye angle point of left eye region, right eye angle point, superior orbit
The left eye angle point on vertex, inferior orbit vertex and/or right eye region, right eye angle point, superior orbit vertex, inferior orbit vertex.This implementation
It is that 24 ocular characteristic points are extracted from 106 face area characteristic points, including 12 of left eye region in example
12 characteristic points of characteristic point and right eye region, as shown in figure 4, in 12 characteristic points, the left eye angle point, right eye angle point,
Superior orbit vertex, this four characteristic points of inferior orbit vertex play a major role to the diffusion deformation of ocular.
The ocular characteristic point is carried out according to preset diffusion ratio to external diffusion in the step 30
It calculates, calculation formula is as follows：
New Points=Old Points+ (Old Points+Center Points) * t%；
Wherein, New Points refer to the coordinate value of the left eye region characteristic point or right eye region characteristic point after diffusion,
Old Points refer to the coordinate value of the corresponding left eye region characteristic point or right eye region characteristic point before diffusion, Center
Points refers to the coordinate value of left eye central point or right eye central point, and t% refers to diffusion ratio；Wherein, t is manually adjusted
The value range of parameter, t is 0~100, and the present embodiment is preferably 20.
The computational methods of the coordinate value of the left eye central point or right eye central point are as follows：
Center Points=Sum (Old Points)/Num；
Wherein, Sum (Old Points) refers to the seat of the left eye region characteristic point or right eye region characteristic point before diffusion
The sum of scale value, Num are the quantity of corresponding left eye region characteristic point or right eye region characteristic point, and Center Points are meter
The coordinate value of obtained left eye central point or right eye central point.
According to the position of the ocular characteristic point before diffusion and after diffusion to described pending in the step 40
Image carry out feature based point anamorphose algorithm processing obtain ocular amplify effect image, further comprise with
Lower step：
41. calculating all facial regions of pending image according to the position of the ocular characteristic point before diffusion and after diffusion
Motion-vector dx and dy of the characteristic of field point in horizontal and vertical both direction.
42. calculating the color of each pixel of effect image according to the motion-vector of the face area characteristic point
Value.
Wherein, step 42 calculates the coordinate value of the pixel on deformed effect image according to following formula first, then
Assign the color value of the corresponding pixel points on the pending image before deformation to the respective pixel on the deformed effect image
Point is to get to the color value of each pixel of effect image.The coordinate value of each pixel of deformed effect image
Calculation formula is as follows：
Wherein, R (x, y) is the coordinate value of pixel of the effect image on [x, y] coordinate；I is right in pending image
The coordinate value of pixel, n is answered to refer to that the number of characteristic point, w (i) are the weights of characteristic point i；The calculation formula of the weight w (i)
For：
For each pixel of effect image, can all be influenced by each feature point deformation, therefore each pixel
Value after point deformation is deviated the weighted sum influenced by each characteristic point before being equal to deformation；Wherein, weight calculation formula
Basic principle is：Distance feature point distance is remoter, and weight is smaller, otherwise bigger.
The present embodiment carries out deformation operation using 106 all points of face area, due to 24 in addition to ocular
Except a point, other points all do not change, therefore can only be deformed to ocular, but other points not changed are still
Above-mentioned calculating is participated in, effect is to ensure that other face areas except ocular do not deform, and get over apart from eyes
Far, the amplitude of deformation is smaller, is the process of a gradual change.
After the processing for carrying out the anamorphose algorithm of feature based point in the step 40 to the pending image,
Processing further also is sharpened to deformed image, to restore the level of sharpness before deforming, USM can be used in the method for sharpening
It sharpens, Roberts gradient operators sharpen, Prewitt gradient operators sharpen, Sobel operators sharpen or Laplacian operators are sharp
Change etc..
As shown in Fig. 2, the present invention also provides a kind of eyes image processing system 100 based on anamorphose comprising：
Face recognition module 101 obtains face area characteristic point for carrying out recognition of face to pending image；
Ocular feature point extraction module 102, for extracting ocular from the face area characteristic point
Characteristic point；
Computing module 103 is spread, it is outside for being carried out according to preset diffusion ratio to the ocular characteristic point
The calculating of diffusion；
Warped processing module 104 is used for the position according to the ocular characteristic point before diffusion and after diffusion to described
Pending image carries out the processing of the anamorphose algorithm of feature based point, obtains the effect image of ocular amplification.
Further include Edge contrast module 105 in the present embodiment, for being sharpened processing to deformed image.
As shown in figure 3, the present invention also provides a kind of camera terminal 200, which includes being based on as described above
The eyes image processing system 100 of anamorphose, wherein the eyes image processing system 100 based on anamorphose may be used
The structure of Fig. 2 embodiments accordingly can execute the technical solution of embodiment of the method shown in Fig. 1, realization principle and technology
Effect is similar, may refer to the related record in above-described embodiment in detail, details are not described herein again.
The camera terminal 200 includes：The equipment that mobile phone, digital camera or tablet computer etc. are configured with camera.
It should be noted that each embodiment in this specification is described in a progressive manner, each embodiment weight
Point explanation is all difference from other examples, and the same or similar parts between the embodiments can be referred to each other.
For system embodiment and terminal embodiment, since it is basically similar to the method embodiment, so description is fairly simple,
The relevent part can refer to the partial explaination of embodiments of method.Also, herein, the terms "include", "comprise" or its
What his variant is intended to non-exclusive inclusion, so that including the processes of a series of elements, method, article or setting
Standby includes not only those elements, but also includes other elements that are not explicitly listed, or further includes for this process, side
Method, article or the intrinsic element of equipment.In the absence of more restrictions, limited by sentence "including a ..."
Element, it is not excluded that there is also other identical elements in the process, method, article or apparatus that includes the element.Separately
Outside, one of ordinary skill in the art will appreciate that realizing that all or part of step of above-described embodiment can be by hardware come complete
At relevant hardware can also being instructed to complete by program, the program can be stored in a kind of computer-readable storage
In medium, storage medium mentioned above can be read-only memory, disk or CD etc..
The preferred embodiment of the present invention has shown and described in above description, it should be understood that the present invention is not limited to this paper institutes
The form of disclosure is not to be taken as excluding other embodiments, and can be used for other combinations, modifications, and environments, and energy
Enough in this paper invented the scope of the idea, modifications can be made through the above teachings or related fields of technology or knowledge.And people from this field
The modifications and changes that member is carried out do not depart from the spirit and scope of the present invention, then all should be in the protection of appended claims of the present invention
In range.
Claims (10)
1. a kind of eyes image processing method based on anamorphose, which is characterized in that include the following steps：
10. a pair pending image carries out recognition of face, face area characteristic point is obtained；
20. extracting ocular characteristic point from the face area characteristic point；
30. the ocular characteristic point described in pair carries out the calculating to external diffusion according to preset diffusion ratio；
40. carrying out feature based to the pending image according to the position of the ocular characteristic point before diffusion and after diffusion
The processing of the anamorphose algorithm of point obtains the effect image of ocular amplification；
The calculating to external diffusion is carried out according to preset diffusion ratio to the ocular characteristic point in the step 30,
Its calculation formula is as follows：
New Points=Old Points+ (Old Points+Center Points) * t%；
Wherein, New Points refer to the coordinate value of the left eye region characteristic point or right eye region characteristic point after diffusion, Old
Points refers to the coordinate value of the corresponding left eye region characteristic point or right eye region characteristic point before diffusion, Center
Points refers to the coordinate value of left eye central point or right eye central point, and t% refers to diffusion ratio.
2. a kind of eyes image processing method based on anamorphose according to claim 1, it is characterised in that：Described
Face area characteristic point is obtained in step 10, refers to that characteristic point or the face of the acquisition face area adjacent with ocular are whole
The characteristic point of body region.
3. a kind of eyes image processing method based on anamorphose according to claim 1, it is characterised in that：Described
Ocular characteristic point in step 20, including the left eye angle point of left eye region, right eye angle point, superior orbit vertex, inferior orbit top
Point and/or the left eye angle point of right eye region, right eye angle point, superior orbit vertex, inferior orbit vertex.
4. a kind of eyes image processing method based on anamorphose according to claim 1, it is characterised in that：Described
The computational methods of the coordinate value of left eye central point or right eye central point are as follows：
Center Points=Sum (Old Points)/Num；
Wherein, Sum (Old Points) refers to the coordinate value of the left eye region characteristic point or right eye region characteristic point before diffusion
Sum, Num is the quantity of corresponding left eye region characteristic point or right eye region characteristic point, and Center Points are to calculate
The coordinate value of the left eye central point or right eye central point that arrive.
5. a kind of eyes image processing method based on anamorphose according to claim 1, it is characterised in that：Described
The pending image is carried out based on spy according to the position of the ocular characteristic point before diffusion and after diffusion in step 40
The processing for levying the anamorphose algorithm of point obtains the effect image of ocular amplification, further comprises the steps：
41. all face areas for calculating pending image according to the position of the ocular characteristic point before diffusion and after diffusion are special
Motion-vector dx and dy of the sign point in horizontal and vertical both direction；
42. calculating the color value of each pixel of effect image according to the motion-vector of the face area characteristic point.
6. a kind of eyes image processing method based on anamorphose according to any one of claims 1 to 5, feature exist
In：After the processing for carrying out the anamorphose algorithm of feature based point in the step 40 to the pending image, also into
One step is sharpened processing to deformed image.
7. a kind of eyes image processing system based on anamorphose, which is characterized in that including：
Face recognition module obtains face area characteristic point for carrying out recognition of face to pending image；
Ocular feature point extraction module, for extracting ocular characteristic point from the face area characteristic point；
Computing module is spread, by being carried out based on to external diffusion according to preset diffusion ratio to the ocular characteristic point
It calculates；The calculation formula to external diffusion is as follows：
New Points=Old Points+ (Old Points+Center Points) * t%；
Wherein, New Points refer to the coordinate value of the left eye region characteristic point or right eye region characteristic point after diffusion, Old
Points refers to the coordinate value of the corresponding left eye region characteristic point or right eye region characteristic point before diffusion, Center
Points refers to the coordinate value of left eye central point or right eye central point, and t% refers to diffusion ratio；
Warped processing module is used for the position according to the ocular characteristic point before diffusion and after diffusion to the pending figure
As the processing for the anamorphose algorithm for carrying out feature based point, the effect image of ocular amplification is obtained.
8. a kind of eyes image processing system based on anamorphose according to claim 7, it is characterised in that：Further include
Edge contrast module, for being sharpened processing to deformed image.
9. a kind of camera terminal, which is characterized in that include eye of claim 7 to 8 any one of them based on anamorphose
Image processing system.
10. camera terminal according to claim 9, which is characterized in that the camera terminal includes：Mobile phone, digital camera
Or tablet computer.
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| CN102375974A (en) * | 2010-08-06 | 2012-03-14 | 佳能株式会社 | Information processing apparatus and information processing method |
| JP2012088538A (en) * | 2010-10-20 | 2012-05-10 | Casio Comput Co Ltd | Image display device and program |
| CN103745429A (en) * | 2013-08-22 | 2014-04-23 | 厦门美图移动科技有限公司 | Method for rapidly realizing eye image processing |
| CN104853134A (en) * | 2014-02-13 | 2015-08-19 | 腾讯科技（深圳）有限公司 | Video communication method and video communication device |
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