CN105160329A - Tooth identification method and system based on YUV color space, and shooting terminal - Google Patents
Tooth identification method and system based on YUV color space, and shooting terminal Download PDFInfo
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- CN105160329A CN105160329A CN201510595449.1A CN201510595449A CN105160329A CN 105160329 A CN105160329 A CN 105160329A CN 201510595449 A CN201510595449 A CN 201510595449A CN 105160329 A CN105160329 A CN 105160329A
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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
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/162—Detection; Localisation; Normalisation using pixel segmentation or colour matching
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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
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/165—Detection; Localisation; Normalisation using facial parts and geometric relationships
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Abstract
The invention discloses a tooth identification method and system based on YUV color space, and a shooting terminal. The method is characterized by collecting tooth sample data, converting the tooth sample data into the YUV color space and carrying out tooth modeling to obtain a tooth model graph; carrying out face identification and tooth primary positioning on an image to be processed to obtain a mouth area comprising teeth; carrying out YUV color space conversion on the mouth area to obtain a converted imaged; and finally, obtaining tooth probability value corresponding to each pixel point of the converted imaged by searching the tooth model graph, and thus a tooth probability graph is obtained. Therefore, quick and automatic tooth identification is realized.
Description
Technical field
The present invention relates to technical field of image processing, particularly system, the camera terminal of a kind of tooth recognition methods based on YUV color space and application the method thereof.
Background technology
Along with the progress of science and technology, more and more equipment being loaded with high definition or minisize pick-up head or image acquiring device occurs, such as digital camera, mobile phone, panel computer, or even notebook etc.Be that the I/O performance etc. of the light of the pixel of picture pick-up device, aperture or shooting environmental, smoothness or even equipment all can impact image quality, the result brought is that imaging and real world real picture have gap.This gap may be disagreed with the wish of equipment user, or does not reach the aesthetic of user.The various image post-processed softwares be derived thus, by carrying out on color process by image, effect image visually being reached compare former figure and more meet user's aesthetic conceptions.
Particularly in the character image process such as certainly to take pictures, even if the treatment effect such as the colour of skin, eyes is all very perfect, a bite is xanthodont always to spoil the fun very much, even if smile is sweet again, but seem after taking pictures that visual impression is always not good enough, make photo overshadowed, therefore dental prosthetics technology is technology smaller but very crucial in image beautifying technique, and dental prosthetics technology depends on tooth recognition technology especially.
Summary of the invention
The present invention, for solving the problem, provides a kind of tooth recognition methods based on YUV color space, system and camera terminal, can carry out tooth identification fast, automatically, is convenient to carry out dental procedure further.
For achieving the above object, the technical solution used in the present invention is:
First, the invention provides a kind of tooth recognition methods based on YUV color space, it comprises the following steps:
10. collect tooth samples data, and these tooth samples data are converted to YUV color space carry out tooth modeling, obtain tooth model figure;
20. pairs of pending images carry out recognition of face, and carry out tooth Primary Location according to the human face region recognized, and obtain the mouth region comprising tooth;
Mouth region described in 30. pairs carries out the conversion of YUV color space, obtains converted image;
40., by searching described tooth model figure, obtain the tooth probable value that each pixel of described converted image is corresponding, thus obtain tooth probability graph.
Preferably, tooth samples data are converted to YUV color space and carry out tooth modeling by described step 10, further comprising the steps:
11. by tooth samples data genaration mask figure;
12. obtain effective tooth pixel corresponding to described tooth samples data according to described mask figure;
Described effective tooth pixel is YUV color space from RGB color space conversion by 13., obtains U component and the V component of described effective tooth pixel.
Preferably, the making of the tooth model figure in described step 10 is further comprising the steps:
14. initialization one black figure are as initial tooth model figure, and this initial tooth model figure is respectively using U component and V component as horizontal ordinate and ordinate;
15. carry out the drafting of tooth model figure according to the U component of described effective tooth pixel and V component, and the location of pixels [U, V] of described effective tooth pixel is set to white;
16. carry out the filling of tooth pixel region by effective tooth pixel of a large amount of tooth samples data, obtain the tooth model figure in later stage.
Preferably, the making of the tooth model figure of described step 10 comprises further carries out manual fine-tuning to the tooth model figure in described later stage, the tooth model figure be optimized; Trim step is as follows:
The black color dots of scattered distribution in the tooth pixel region of the white of drawing in black figure carries out being filled to white by 17.;
18. reject the white point far away with described tooth pixel region deviation;
The edge of the tooth pixel region described in 19. pairs carries out gradual change process, the tooth model figure be optimized.
Preferably, carry out according to the human face region recognized the mouth region that tooth Primary Location obtains comprising tooth in described step 20, it is the key point of the mouth region by identifying described human face region, and carry out image cropping by the boundary rectangle of this key point, obtain the mouth region comprising tooth.
Preferably, described tooth model figure is searched in described step 40, it is the coordinate position carrying out the correspondence of the tooth model figure searching described YUV color space according to the U component of the converted image of described YUV color space and V component, wherein, described tooth model figure is using U component and V component as its horizontal ordinate and ordinate.
Preferably, obtain tooth probable value corresponding to each pixel of described converted image by searching described tooth model figure in described step 40, the computing formula of this tooth probable value is as follows:
Alpha＝TeethModel[U*256+V]；
Wherein, U, V are respectively U component and the V component of each pixel of described converted image, the tooth probable value of TeethModel to be described tooth model figure, Alpha the be corresponding pixel points calculated.
Secondly, the present invention also provides a kind of tooth recognition system based on YUV color space, and it comprises:
Tooth model figure creation module, it is by collecting tooth samples data, and these tooth samples data are converted to YUV color space carry out tooth modeling, obtains tooth model figure;
Face recognition module, it by carrying out recognition of face to pending image, and carries out tooth Primary Location according to the human face region recognized, and obtains the mouth region comprising tooth;
Color-space conversion module, it carries out the conversion of YUV color space to described mouth region, obtains converted image;
Tooth probability evaluation entity, it, by searching described tooth model figure, obtains the tooth probable value that each pixel of described converted image is corresponding, thus obtains tooth probability graph.
In addition, the present invention also provides a kind of camera terminal, it is characterized in that, this camera terminal comprises as above based on the tooth recognition system of YUV color space.
Preferably, described camera terminal comprises: mobile phone, digital camera or panel computer.
The invention has the beneficial effects as follows:
A kind of tooth recognition methods based on YUV color space of the present invention, system and camera terminal, it is by collecting tooth samples data, and these tooth samples data are converted to YUV color space and carry out tooth modeling and obtain tooth model figure, then recognition of face and tooth Primary Location are carried out to pending image, obtain the mouth region comprising tooth, and YUV color space carries out to described mouth region be converted to converted image, tooth probable value corresponding to each pixel of described converted image is obtained finally by searching described tooth model figure, thus obtain tooth probability graph, realize fast, carry out tooth identification automatically.
Accompanying drawing explanation
Accompanying drawing described herein is used to provide a further understanding of the present invention, forms a part of the present invention, and schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the general flow chart of the tooth recognition methods that the present invention is based on YUV color space;
Fig. 2 is the structural representation of the tooth recognition system that the present invention is based on YUV color space;
Fig. 3 is the structural representation of camera terminal of the present invention;
Fig. 4 is the pending image of the present invention one specific embodiment;
Fig. 5 is the tooth model figure of a preferred embodiment of the present invention;
Fig. 6 be carry out the tooth model figure of Fig. 5 according to the pending image of the inventive method to Fig. 4 search the tooth probability graph obtained.
Embodiment
For making the object of the embodiment of the present invention, technical scheme and advantage clearly, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, instead of whole embodiments.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
As shown in Figure 1, a kind of tooth recognition methods based on YUV color space of the present invention, it comprises the following steps:
10. collect tooth samples data, and these tooth samples data are converted to YUV color space carry out tooth modeling, obtain tooth model figure;
20. pairs of pending images carry out recognition of face, and carry out tooth Primary Location according to the human face region recognized, and obtain the mouth region comprising tooth;
Mouth region described in 30. pairs carries out the conversion of YUV color space, obtains converted image;
40., by searching described tooth model figure, obtain the tooth probable value that each pixel of described converted image is corresponding, thus obtain tooth probability graph.
In the present embodiment, tooth samples data are converted to YUV color space and carry out tooth modeling by described step 10, further comprising the steps:
11. by tooth samples data genaration mask figure, the present embodiment adopts PS instrument demarcate the active component of respective tooth one by one to described tooth samples data and generate mask figure, represent tooth regions by white in this mask figure, represent other regions with black;
12. obtain effective tooth pixel corresponding to described tooth samples data according to described mask figure;
Described effective tooth pixel is YUV color space from RGB color space conversion by 13., obtains U component and the V component of described effective tooth pixel; Specific formula for calculation is as follows:
Y＝R*0.299000+G*0.587000+B*0.114000；
U＝R*-0.168736+G*-0.331264+B*0.500000+128；
V＝R*0.500000+G*-0.418688+B*-.081312+128；
Wherein, R, G, B are the pixel value of each passage of tooth pixel under RGB color space, and Y, U, V are the pixel value under corresponding YUV color space, and R, G, B, Y, U, V span is between 0 to 255.
In the present embodiment, the making of described tooth model figure is further comprising the steps:
14. initialization one black figure are as initial tooth model figure, and this initial tooth model figure size is 256*256, and it is respectively using U component and V component as horizontal ordinate and ordinate;
15. carry out the drafting of tooth model figure according to the U component of described effective tooth pixel and V component, and the location of pixels [U, V] of described effective tooth pixel is set to white;
16. carry out the filling of tooth pixel region by effective tooth pixel of a large amount of tooth samples data, obtain the tooth model figure in later stage.
Due to the finiteness of tooth samples data, may also there are some deviations in the tooth model figure in described later stage.Overcoming these deviations except increasing tooth samples data, considering efficiency factor, further can also carry out manual fine-tuning to the tooth model figure in described later stage, the tooth model figure be optimized; Trim step is as follows:
The black color dots of scattered distribution in the tooth pixel region of the white of drawing in black figure carries out being filled to white by 17.;
18. reject the white point far away with described tooth pixel region deviation;
The edge of the tooth pixel region described in 19. pairs carries out gradual change process, the tooth model figure be optimized.
Carry out according to the human face region recognized the mouth region that tooth Primary Location obtains comprising tooth in described step 20, it is the key point of the mouth region by identifying described human face region, and carry out image cropping by the boundary rectangle of this key point, obtain the mouth region (as shown in Figure 4) comprising tooth.
Described tooth model figure (as shown in Figure 5) is searched in described step 40, it is the coordinate position carrying out the correspondence of the tooth model figure searching described YUV color space according to the U component of the converted image of described YUV color space and V component, wherein, described tooth model figure is using U component and V component as its horizontal ordinate and ordinate.The computing formula of described tooth probable value is as follows:
Alpha＝TeethModel[U*256+V]；
Wherein, U, V are respectively U component and the V component of each pixel of described converted image, the tooth probable value of TeethModel to be described tooth model figure, Alpha the be corresponding pixel points calculated.The tooth probable value of all pixels of the converted image described in being calculated by above method, namely obtain the tooth probability graph (as shown in Figure 6) that this converted image is corresponding, various whitening process or other process can be carried out to tooth easily according to this tooth probability graph.
As shown in Figure 2, the present invention also provides a kind of tooth recognition system 100 based on YUV color space, and it comprises:
Tooth model figure creation module 101, it is by collecting tooth samples data, and these tooth samples data are converted to YUV color space carry out tooth modeling, obtains tooth model figure;
Face recognition module 102, it by carrying out recognition of face to pending image, and carries out tooth Primary Location according to the human face region recognized, and obtains the mouth region comprising tooth;
Color-space conversion module 103, it carries out the conversion of YUV color space to described mouth region, obtains converted image;
Tooth probability evaluation entity 104, it, by searching described tooth model figure, obtains the tooth probable value that each pixel of described converted image is corresponding, thus obtains tooth probability graph.
As shown in Figure 3, the present invention also provides a kind of camera terminal 200, this camera terminal 200 comprises as above based on the tooth recognition system 100 of YUV color space, wherein, the tooth recognition system 100 based on YUV color space can adopt the structure of Fig. 2 embodiment, and it accordingly, the technical scheme of embodiment of the method shown in Fig. 1 can be performed, it realizes principle and technique effect is similar, see the relevant record in above-described embodiment, can repeat no more in detail herein.
Described camera terminal comprises: mobile phone, digital camera or panel computer etc. are configured with the equipment of camera.
It should be noted that, each embodiment in this instructions all adopts the mode of going forward one by one to describe, and what each embodiment stressed is the difference with other embodiments, between each embodiment identical similar part mutually see.For system embodiment and terminal embodiment, due to itself and embodiment of the method basic simlarity, so description is fairly simple, relevant part illustrates see the part of embodiment of the method.And, in this article, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thus make to comprise the process of a series of key element, method, article or equipment and not only comprise those key elements, but also comprise other key elements clearly do not listed, or also comprise by the intrinsic key element of this process, method, article or equipment.When not more restrictions, the key element limited by statement " comprising ... ", and be not precluded within process, method, article or the equipment comprising described key element and also there is other identical element.In addition, one of ordinary skill in the art will appreciate that all or part of step realizing above-described embodiment can have been come by hardware, the hardware that also can carry out instruction relevant by program completes, described program can be stored in a kind of computer-readable recording medium, the above-mentioned storage medium mentioned can be ROM (read-only memory), disk or CD etc.
Above-mentioned explanation illustrate and describes the preferred embodiments of the present invention, be to be understood that the present invention is not limited to the form disclosed by this paper, should not regard the eliminating to other embodiments as, and can be used for other combinations various, amendment and environment, and can in invention contemplated scope herein, changed by the technology of above-mentioned instruction or association area or knowledge.And the change that those skilled in the art carry out and change do not depart from the spirit and scope of the present invention, then all should in the protection domain of claims of the present invention.
Claims (10)
1., based on a tooth recognition methods for YUV color space, it is characterized in that, comprise the following steps:
10. collect tooth samples data, and these tooth samples data are converted to YUV color space carry out tooth modeling, obtain tooth model figure;
20. pairs of pending images carry out recognition of face, and carry out tooth Primary Location according to the human face region recognized, and obtain the mouth region comprising tooth;
Mouth region described in 30. pairs carries out the conversion of YUV color space, obtains converted image;
40., by searching described tooth model figure, obtain the tooth probable value that each pixel of described converted image is corresponding, thus obtain tooth probability graph.
2. a kind of tooth recognition methods based on YUV color space according to claim 1, is characterized in that: tooth samples data are converted to YUV color space and carry out tooth modeling by described step 10, further comprising the steps:
11. by tooth samples data genaration mask figure;
12. obtain effective tooth pixel corresponding to described tooth samples data according to described mask figure;
Described effective tooth pixel is YUV color space from RGB color space conversion by 13., obtains U component and the V component of described effective tooth pixel.
3. a kind of tooth recognition methods based on YUV color space according to claim 2, is characterized in that: the making of the tooth model figure in described step 10 is further comprising the steps:
14. initialization one black figure are as initial tooth model figure, and this initial tooth model figure is respectively using U component and V component as horizontal ordinate and ordinate;
15. carry out the drafting of tooth model figure according to the U component of described effective tooth pixel and V component, and the location of pixels [U, V] of described effective tooth pixel is set to white;
16. carry out the filling of tooth pixel region by effective tooth pixel of a large amount of tooth samples data, obtain the tooth model figure in later stage.
4. a kind of tooth recognition methods based on YUV color space according to claim 3, it is characterized in that: the making of the tooth model figure of described step 10 comprises further carries out manual fine-tuning to the tooth model figure in described later stage, the tooth model figure be optimized; Trim step is as follows:
The black color dots of scattered distribution in the tooth pixel region of the white of drawing in black figure carries out being filled to white by 17.;
18. reject the white point far away with described tooth pixel region deviation;
The edge of the tooth pixel region described in 19. pairs carries out gradual change process, the tooth model figure be optimized.
5. a kind of tooth recognition methods based on YUV color space according to claim 1 or 2 or 3 or 4, it is characterized in that: in described step 20, carry out according to the human face region recognized the mouth region that tooth Primary Location obtains comprising tooth, it is the key point of the mouth region by identifying described human face region, and carry out image cropping by the boundary rectangle of this key point, obtain the mouth region comprising tooth.
6. a kind of tooth recognition methods based on YUV color space according to claim 1 or 2 or 3 or 4, it is characterized in that: in described step 40, search described tooth model figure, it is the coordinate position carrying out the correspondence of the tooth model figure searching described YUV color space according to the U component of the converted image of described YUV color space and V component, wherein, described tooth model figure is using U component and V component as its horizontal ordinate and ordinate.
7. a kind of tooth recognition methods based on YUV color space according to claim 1 or 2 or 3 or 4, it is characterized in that: obtain tooth probable value corresponding to each pixel of described converted image by searching described tooth model figure in described step 40, the computing formula of this tooth probable value is as follows:
Alpha＝TeethModel[U*256+V]；
Wherein, U, V are respectively U component and the V component of each pixel of described converted image, the tooth probable value of TeethModel to be described tooth model figure, Alpha the be corresponding pixel points calculated.
8., based on a tooth recognition system for YUV color space, it is characterized in that, comprising:
Tooth model figure creation module, it is by collecting tooth samples data, and these tooth samples data are converted to YUV color space carry out tooth modeling, obtains tooth model figure;
Face recognition module, it by carrying out recognition of face to pending image, and carries out tooth Primary Location according to the human face region recognized, and obtains the mouth region comprising tooth;
Color-space conversion module, it carries out the conversion of YUV color space to described mouth region, obtains converted image;
Tooth probability evaluation entity, it, by searching described tooth model figure, obtains the tooth probable value that each pixel of described converted image is corresponding, thus obtains tooth probability graph.
9. a camera terminal, is characterized in that, comprises the tooth recognition system based on YUV color space according to claim 8.
10. camera terminal according to claim 9, is characterized in that, described camera terminal comprises: mobile phone, digital camera or panel computer.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111028251A (en) * | 2019-12-27 | 2020-04-17 | 四川大学 | Dental picture cutting method, system, equipment and storage medium |
| CN111462114A (en) * | 2020-04-26 | 2020-07-28 | 广州皓醒湾科技有限公司 | Tooth color value determination method and device and electronic equipment |
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| CN1516074A (en) * | 2002-12-28 | 2004-07-28 | ���ǵ�����ʽ���� | Method for extracting tooth area from tooth image and personal recongition method and device |
| CN101933047A (en) * | 2008-02-01 | 2010-12-29 | 惠普开发有限公司 | Teeth locating and whitening in a digital image |
| US20150213622A1 (en) * | 2014-01-29 | 2015-07-30 | Abdullaibrahim Abdulwaheed | Measuring Teeth Whiteness System and Method |
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| CN1516074A (en) * | 2002-12-28 | 2004-07-28 | ���ǵ�����ʽ���� | Method for extracting tooth area from tooth image and personal recongition method and device |
| CN101933047A (en) * | 2008-02-01 | 2010-12-29 | 惠普开发有限公司 | Teeth locating and whitening in a digital image |
| US20150213622A1 (en) * | 2014-01-29 | 2015-07-30 | Abdullaibrahim Abdulwaheed | Measuring Teeth Whiteness System and Method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111028251A (en) * | 2019-12-27 | 2020-04-17 | 四川大学 | Dental picture cutting method, system, equipment and storage medium |
| CN111462114A (en) * | 2020-04-26 | 2020-07-28 | 广州皓醒湾科技有限公司 | Tooth color value determination method and device and electronic equipment |
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