CN109902635A - A kind of portrait signature identification method based on example graph - Google Patents
A kind of portrait signature identification method based on example graph Download PDFInfo
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- CN109902635A CN109902635A CN201910161830.5A CN201910161830A CN109902635A CN 109902635 A CN109902635 A CN 109902635A CN 201910161830 A CN201910161830 A CN 201910161830A CN 109902635 A CN109902635 A CN 109902635A
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- 238000000034 method Methods 0.000 title claims abstract description 52
- 230000000877 morphologic effect Effects 0.000 claims abstract description 44
- 230000037303 wrinkles Effects 0.000 claims abstract description 16
- 230000003542 behavioural effect Effects 0.000 claims abstract description 14
- 210000003128 head Anatomy 0.000 claims description 21
- 230000001815 facial effect Effects 0.000 claims description 8
- 210000001331 nose Anatomy 0.000 claims description 8
- 210000004709 eyebrow Anatomy 0.000 claims description 6
- GNFTZDOKVXKIBK-UHFFFAOYSA-N 3-(2-methoxyethoxy)benzohydrazide Chemical compound COCCOC1=CC=CC(C(=O)NN)=C1 GNFTZDOKVXKIBK-UHFFFAOYSA-N 0.000 claims description 5
- FGUUSXIOTUKUDN-IBGZPJMESA-N C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 Chemical compound C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 FGUUSXIOTUKUDN-IBGZPJMESA-N 0.000 claims description 5
- YTAHJIFKAKIKAV-XNMGPUDCSA-N [(1R)-3-morpholin-4-yl-1-phenylpropyl] N-[(3S)-2-oxo-5-phenyl-1,3-dihydro-1,4-benzodiazepin-3-yl]carbamate Chemical compound O=C1[C@H](N=C(C2=C(N1)C=CC=C2)C1=CC=CC=C1)NC(O[C@H](CCN1CCOCC1)C1=CC=CC=C1)=O YTAHJIFKAKIKAV-XNMGPUDCSA-N 0.000 claims description 5
- 230000005021 gait Effects 0.000 claims description 5
- 210000000216 zygoma Anatomy 0.000 claims description 4
- 210000004209 hair Anatomy 0.000 claims description 3
- 210000002454 frontal bone Anatomy 0.000 claims description 2
- 210000002050 maxilla Anatomy 0.000 claims description 2
- 210000000537 nasal bone Anatomy 0.000 claims description 2
- 210000000103 occipital bone Anatomy 0.000 claims description 2
- 210000003455 parietal bone Anatomy 0.000 claims description 2
- 210000003582 temporal bone Anatomy 0.000 claims description 2
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 238000010276 construction Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 7
- 241001300198 Caperonia palustris Species 0.000 description 2
- 235000000384 Veronica chamaedrys Nutrition 0.000 description 2
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Abstract
The portrait signature identification method based on example graph that the invention discloses a kind of, it is primarily characterized in that through the genealogical classification to portrait feature, and respective example graph identifier is formulated to various portrait features, user can choose corresponding portrait examples of features figure and be placed in the effective mark realized at the portrait feature locations for needing to identify to the portrait feature；Portrait feature is divided into head morphological feature, face morphological feature, face configuration relation feature, beard feature, wrinkle feature, face behavioral characteristics, aspectual character, human body special marking feature, human dressing feature, human body baldric feature etc..The beneficial effects of the present invention are: the present invention has carried out genealogical classification to portrait feature；The present invention is to different portrait feature construction example graph groups, and user can be to select character pair example effectively to identify portrait feature in the slave example graph group of efficient quick, and the aspect ratio convenient for the portrait identification later period is presented to result.
Description
Technical field
The portrait signature identification method based on example graph that the present invention relates to a kind of, this method use predetermined
Portrait examples of features figure carries out efficient identification to the portrait feature that portrait in judicial expertise is identified.
Background technique
Portrait identification in judicial expertise refers to that, by comparing, analysis, the identity of human body recorded to audio-visual data is asked
Inscribe carried out science judgment；And portrait refers to the human body appearance image in audio-visual data by the means record such as photograph, camera shooting,
Wherein, portrait feature refers to the specific sign of human body appearance each section growth characteristic and its exercise habit.Portrait feature can divide
For head morphological feature, face morphological feature, face configuration relation feature, beard feature, wrinkle feature, face behavioral characteristics,
Aspectual character, human body special marking feature, human dressing feature, human body baldric feature etc..It needs in portrait identification to sample people
The portrait feature reflected in picture and sample portrait is effectively identified, with the portrait aspect ratio in being identified for portrait to
Portrait feature is presented.
Summary of the invention
For fields such as judicial evidence collection and judicial expertises to the portrait signature identification method demand in portrait identification, the present invention
A kind of portrait signature identification method based on example graph is provided.
The present invention solves technological means used by technical problem are as follows:
A kind of portrait signature identification method based on example graph, wherein include the following steps:
Step a, portrait feature is divided into following organic component, including head morphological feature, face morphological feature, five
Official's configuration relation feature, beard feature, wrinkle feature, face behavioral characteristics, aspectual character, human body special marking feature, human body
Dressing feature, human body baldric feature etc., user can optionally selectively be identified above-mentioned portrait feature；
Step b, input includes the image of portrait, is labeled as JC；
Step c, JC image is rotated and is scaled, make the eyes position horizontal position of the facial image in JC image
It sets, facial image size is suitable；
Step d, optionally head morphological feature is identified, user selects suitable head form example graph to place
Near the corresponding feature locations of corresponding JC image, and lines extension and identification characteristics can be passed through in example graph position periphery
Type；
Step e, optionally face morphological feature is identified, user selects suitable face form example graph to place
Near the corresponding feature locations of corresponding JC image, and lines extension and identification characteristics can be passed through in example graph position periphery
Type；
Step f, optionally face configuration relation feature is identified, user selects suitable face configuration relation example
Figure is placed near the corresponding feature locations of corresponding JC image, and can be extended simultaneously in example graph position periphery by lines
Identification characteristics type；
Step g, optionally beard feature is identified, user selects suitable beard example graph to be placed in accordingly
Near the corresponding feature locations of JC image, and lines extension and identification characteristics type can be passed through in example graph position periphery；
Step h, optionally wrinkle feature is identified, user selects suitable wrinkle example graph to be placed in accordingly
Near the corresponding feature locations of JC image, and lines extension and identification characteristics type can be passed through in example graph position periphery；
Step i, optionally face behavioral characteristics are identified, user selects suitable face dynamic example graph to place
Near the corresponding feature locations of corresponding JC image, and lines extension and identification characteristics can be passed through in example graph position periphery
Type；
Step j, optionally aspectual character is identified, user selects suitable posture example graph to be placed in accordingly
Near the corresponding feature locations of JC image, and lines extension and identification characteristics type can be passed through in example graph position periphery；
Step k, optionally human body special marking feature is identified, user selects suitable human body special marking example
Figure is placed near the corresponding feature locations of corresponding JC image, and can be extended simultaneously in example graph position periphery by lines
Identification characteristics type；
Step l, optionally human dressing feature is identified, user selects suitable human dressing example graph to place
Near the corresponding feature locations of corresponding JC image, and lines extension and identification characteristics can be passed through in example graph position periphery
Type；
Step m, optionally human body baldric feature is identified, user selects suitable human body baldric example graph to place
Near the corresponding feature locations of corresponding JC image, and lines extension and identification characteristics can be passed through in example graph position periphery
Type.
The above-mentioned portrait signature identification method based on example graph, wherein the head morphological feature referred in the step d
Identification method, head morphological feature mainly include brainpan morphological feature and face morphological feature, wherein brainpan morphological feature includes
The forms such as frontal bone, temporal bone, parietal bone, the occipital bone of neurocranium part face feature reflect, face morphological feature include cheekbone, nasal bone,
The forms such as maxilla, mandibular reflect in the feature of face, can specifically show as hair style, hair line, cheekbone portion, cheek, lower jaw
Etc. morphological features；Each module diagnostic includes corresponding example graph group in the morphological feature of head, and user can be from exemplary diagram
Corresponding example graph is selected to be identified individual features in JC image in shape group.
The above-mentioned portrait signature identification method based on example graph, wherein the face morphological feature referred in the step e
Identification method, face morphological feature mainly include eye, eyebrow, ear, mouth, nose morphological feature, eye in face morphological feature, eyebrow, ear,
Mouth, nasal assembly feature include corresponding example graph group, and user can select corresponding example graph from example graph group
Individual features in JC image are identified.
The above-mentioned portrait signature identification method based on example graph, wherein the face configuration relation referred in the step f
Signature identification method, face configuration relation feature mainly include the components such as volume, eye, eyebrow, ear, mouth, nose in face's grid scale and
Longitudinal proportionate relationship morphological feature, grid scale and longitudinal proportionate relationship feature include corresponding in face configuration relation feature
Example graph group, user can select corresponding example graph to mark individual features in JC image from example graph group
Know, and identifies specific proportional numerical value.
The above-mentioned portrait signature identification method based on example graph, wherein the beard signature identification referred in the step g
Method, beard feature include corresponding example graph group, and user can select corresponding example graph pair from example graph group
Individual features are identified in JC image.
The above-mentioned portrait signature identification method based on example graph, wherein the wrinkle signature identification referred in the step h
Method, wrinkle feature include corresponding example graph group, and user can select corresponding example graph pair from example graph group
Individual features are identified in JC image.
The above-mentioned portrait signature identification method based on example graph, wherein the face behavioral characteristics referred in the step i
Identification method, face behavioral characteristics include corresponding example graph group, and user can select to show accordingly from example graph group
Example diagram shape is identified individual features in JC image.
The above-mentioned portrait signature identification method based on example graph, wherein the aspectual character mark referred in the step j
Method, aspectual character mainly include head aspectual character, hand aspectual character, body aspectual character, gait feature etc., and posture is special
The features such as head aspectual character, hand aspectual character, body aspectual character, gait feature in sign include corresponding exemplary diagram
Shape group, user can select corresponding example graph to be identified individual features in JC image from example graph group.
The above-mentioned portrait signature identification method based on example graph, wherein the human body special marking referred in the step k
Signature identification method, human body special marking feature mainly include the special marking of facial special marking feature and other positions of human body
Feature, face and the other position component special marking features of human body include corresponding example graph in human body special marking feature
Group, user can select corresponding example graph to be identified individual features in JC image from example graph group.
The above-mentioned portrait signature identification method based on example graph, wherein the human dressing feature referred in the step l
Identification method, human dressing feature include corresponding example graph group, and user can select to show accordingly from example graph group
Example diagram shape is identified individual features in JC image.
The above-mentioned portrait signature identification method based on example graph, wherein the human body baldric feature referred in the step m
Identification method, human body baldric feature include corresponding example graph group, and user can select to show accordingly from example graph group
Example diagram shape is identified individual features in JC image.
The beneficial effects of the present invention are:
1, the present invention has carried out genealogical classification to portrait feature.
2, for the present invention to different portrait feature construction example graph groups, user can be in the slave example graph group of efficient quick
Selection character pair example effectively identifies portrait feature, and the aspect ratio convenient for the portrait identification later period is presented to result.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the portrait signature identification method based on example graph of the present invention.
Specific embodiment
The present invention will be further explained below with reference to the attached drawings and specific examples, but not as the limitation of the invention.
Present embodiments provide a kind of portrait signature identification method based on example graph.Entire workflow such as Fig. 1 institute
Show, the present embodiment includes the following steps:
Step a, portrait feature is divided into following organic component, including head morphological feature, face morphological feature, five
Official's configuration relation feature, beard feature, wrinkle feature, face behavioral characteristics, aspectual character, human body special marking feature, human body
Dressing feature, human body baldric feature etc., user can optionally selectively be identified above-mentioned portrait feature, the present embodiment
In, user needs to be identified the above-mentioned portrait feature referred to；
Step b, input includes the image of portrait, is labeled as JC；
Step c, JC image is rotated and is scaled, make the eyes position horizontal position of the facial image in JC image
It sets, facial image size is suitable；
Step d, head morphological feature is identified, user selects suitably from the morphological feature example graph group of head
Example graph is placed near the corresponding feature locations of corresponding JC image, and is extended in example graph position periphery by lines
And identification characteristics type, in the present embodiment, user has selected the round face exemplary diagram in the shape of face feature in the morphological feature of head
At shape is placed in JC image below face face contour position, and is extended by lines and identify " round face " printed words；
Step e, face morphological feature is identified, user selects suitably from face morphological feature example graph group
Example graph is placed near the corresponding feature locations of corresponding JC image, and is extended in example graph position periphery by lines
And identification characteristics type, in the present embodiment, user has selected the birdeye exemplary diagram in the eye-shaped feature in face morphological feature
Shape is placed in JC image at position of human eye, and is extended by lines and identified " birdeye " printed words, meanwhile, select face shape
Contracting lip example graph in nozzle type feature in state feature is placed in Hp position in JC image, and extends and identify by lines
" contracting lip " printed words；
Step f, face configuration relation feature is identified, user selects from face configuration relation examples of features graphical set
It selects suitable example graph to be placed near the corresponding feature locations of corresponding JC image, and passes through in example graph position periphery
Lines extend and identification characteristics type, and in the present embodiment, user has selected eye, nose, lower jaw group in face configuration relation feature
Part is placed in eye, nose, mandibular location in JC image in the grid scale example graph of face, and extends and identify by lines
" eye nose/nose lower jaw=1.04 " printed words；
Step g, beard feature is identified, user selects suitable example graph from beard examples of features graphical set
It is placed near the corresponding feature locations of corresponding JC image, and is extended in example graph position periphery by lines and identify spy
Type is levied, in the present embodiment, user has selected the beard example graph in beard feature to be placed in face beard in JC image
Near corresponding position, and is extended by lines and identify " beard " printed words；
Step h, wrinkle feature is identified, user selects suitable example graph from wrinkle examples of features graphical set
It is placed near the corresponding feature locations of corresponding JC image, and is extended in example graph position periphery by lines and identify spy
Type is levied, in the present embodiment, user has selected the nasolabial groove example graph in wrinkle feature to be placed in face muffle in JC image
Near ditch position, and is extended by lines and identify " nasolabial groove " printed words；
Step i, face behavioral characteristics are identified, user selects suitably from face behavioral characteristics example graph group
Example graph is placed near the corresponding feature locations of corresponding JC image, and is extended in example graph position periphery by lines
And identification characteristics type, in the present embodiment, user has selected the mouth example graph of closing lightly in face behavioral characteristics to be placed in JC image
Near middle Hp position, and is extended by lines and identify " closing lightly mouth " printed words；
Step j, aspectual character is identified, user selects suitable example graph from aspectual character example graph group
It is placed near the corresponding feature locations of corresponding JC image, and is extended in example graph position periphery by lines and identify spy
Type is levied, in the present embodiment, user has selected the toed-out example graph of gait feature in aspectual character to be placed in JC image
Near human foot position, and is extended by lines and identify " toed-out " printed words；
Step k, human body special marking feature is identified, user selects from human body special marking examples of features graphical set
It selects suitable example graph to be placed near the corresponding feature locations of corresponding JC image, and passes through in example graph position periphery
Lines extend and identification characteristics type, and in the present embodiment, user has selected the facial special marking in human body special marking feature
The mole example graph of feature is placed in JC image near face's corresponding position, and is extended by lines and identified " mole " printed words；
Step l, human dressing feature is identified, user selects suitably from human dressing examples of features graphical set
Example graph is placed near the corresponding feature locations of corresponding JC image, and is extended in example graph position periphery by lines
And identification characteristics type, in the present embodiment, user has selected the necklace example graph in human dressing feature to be placed in JC image
Near middle human body neck position, and is extended by lines and identify " necklace " printed words；
Step m, human body baldric feature is identified, user selects suitably from human body baldric examples of features graphical set
Example graph is placed near the corresponding feature locations of corresponding JC image, and is extended in example graph position periphery by lines
And identification characteristics type, in the present embodiment, user has selected the shoes example graph in human body baldric feature to be placed in JC image
Near middle human foot position, and is extended by lines and identify " shoes " printed words；
The foregoing is merely preferred embodiments of the present invention, are not intended to limit claim of the invention, so
It is all to change with equivalent structure made by description of the invention and diagramatic content, it is included within the scope of protection of the present invention.
Claims (11)
1. a kind of portrait signature identification method based on example graph, which comprises the steps of:
Step a, portrait feature is divided into following organic component, including head morphological feature, face morphological feature, face are matched
Set relationship characteristic, beard feature, wrinkle feature, face behavioral characteristics, aspectual character, human body special marking feature, human dressing
Feature, human body baldric feature etc., user can optionally selectively be identified above-mentioned portrait feature；
Step b, input includes the image of portrait, is labeled as JC；
Step c, JC image is rotated and is scaled, make the eyes position horizontal position of the facial image in JC image, people
Face image size is suitable；
Step d, optionally head morphological feature is identified, user selects suitable head form example graph to be placed in phase
Near the corresponding feature locations of JC image answered, and lines extension and identification characteristics class can be passed through in example graph position periphery
Type；
Step e, optionally face morphological feature is identified, user selects suitable face form example graph to be placed in phase
Near the corresponding feature locations of JC image answered, and lines extension and identification characteristics class can be passed through in example graph position periphery
Type；
Step f, optionally face configuration relation feature is identified, user selects suitable face configuration relation example graph
It is placed near the corresponding feature locations of corresponding JC image, and can extend and identify by lines in example graph position periphery
Characteristic type；
Step g, optionally beard feature is identified, user selects suitable beard example graph to be placed in corresponding JC figure
Near corresponding feature locations, and lines extension and identification characteristics type can be passed through in example graph position periphery；
Step h, optionally wrinkle feature is identified, user selects suitable wrinkle example graph to be placed in corresponding JC figure
Near corresponding feature locations, and lines extension and identification characteristics type can be passed through in example graph position periphery；
Step i, optionally face behavioral characteristics are identified, user selects suitable face dynamic example graph to be placed in phase
Near the corresponding feature locations of JC image answered, and lines extension and identification characteristics class can be passed through in example graph position periphery
Type；
Step j, optionally aspectual character is identified, user selects suitable posture example graph to be placed in corresponding JC figure
Near corresponding feature locations, and lines extension and identification characteristics type can be passed through in example graph position periphery；
Step k, optionally human body special marking feature is identified, user selects suitable human body special marking example graph
It is placed near the corresponding feature locations of corresponding JC image, and can extend and identify by lines in example graph position periphery
Characteristic type；
Step l, optionally human dressing feature is identified, user selects suitable human dressing example graph to be placed in phase
Near the corresponding feature locations of JC image answered, and lines extension and identification characteristics class can be passed through in example graph position periphery
Type；
Step m, optionally human body baldric feature is identified, user selects suitable human body baldric example graph to be placed in phase
Near the corresponding feature locations of JC image answered, and lines extension and identification characteristics class can be passed through in example graph position periphery
Type.
2. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step d
And head morphological feature identification method, head morphological feature mainly includes brainpan morphological feature and face morphological feature, wherein
Brainpan morphological feature includes that the forms such as frontal bone, temporal bone, parietal bone, the occipital bone of neurocranium part reflect in the feature of face, face form spy
Feature of the sign comprising forms such as cheekbone, nasal bone, maxilla, mandibulars in face reflects, can specifically show as hair style, hairline
The morphological features such as line, cheekbone portion, cheek, lower jaw；Each module diagnostic includes corresponding example graph group in the morphological feature of head,
User can select corresponding example graph to be identified individual features in JC image from example graph group.
3. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step e
And face morphological feature identification method, face morphological feature mainly includes eye, eyebrow, ear, mouth, nose morphological feature, face form
Eye, eyebrow, ear, mouth, nasal assembly feature include corresponding example graph group in feature, and user can select from example graph group
Corresponding example graph is identified individual features in JC image.
4. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step f
And face configuration relation signature identification method, face configuration relation feature mainly includes the components such as volume, eye, eyebrow, ear, mouth, nose
Grid scale and longitudinal proportionate relationship in face's grid scale and longitudinal proportionate relationship morphological feature, face configuration relation feature
Feature includes corresponding example graph group, and user can select corresponding example graph in JC image from example graph group
Individual features are identified, and identify specific proportional numerical value.
5. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step g
And beard signature identification method, beard feature includes corresponding example graph group, and user can select from example graph group
Corresponding example graph is identified individual features in JC image.
6. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step h
And wrinkle signature identification method, wrinkle feature includes corresponding example graph group, and user can select from example graph group
Corresponding example graph is identified individual features in JC image.
7. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step i
And face behavioral characteristics identification method, face behavioral characteristics include corresponding example graph group, user can be from example graph
Corresponding example graph is selected to be identified individual features in JC image in group.
8. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step j
And aspectual character identification method, aspectual character mainly include head aspectual character, hand aspectual character, body aspectual character,
Gait feature etc., the features such as head aspectual character, hand aspectual character, body aspectual character, gait feature in aspectual character
It include corresponding example graph group, user can select corresponding example graph to corresponding in JC image from example graph group
Feature is identified.
9. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step k
And human body special marking signature identification method, human body special marking feature mainly include facial special marking feature and human body its
The special marking feature at his position, face and the other position component special marking features of human body are wrapped in human body special marking feature
Containing corresponding example graph group, user can select corresponding example graph to individual features in JC image from example graph group
It is identified.
10. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step l
And human dressing signature identification method, human dressing feature include corresponding example graph group, user can be from example graph
Corresponding example graph is selected to be identified individual features in JC image in group.
11. the portrait signature identification method based on example graph as described in claim 1, which is characterized in that mentioned in the step m
And human body baldric signature identification method, human body baldric feature include corresponding example graph group, user can be from example graph
Corresponding example graph is selected to be identified individual features in JC image in group.
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Application publication date: 20190618 |