CN109657527B - Painting brush touch identification system and method - Google Patents
Painting brush touch identification system and method Download PDFInfo
- Publication number
- CN109657527B CN109657527B CN201710947483.XA CN201710947483A CN109657527B CN 109657527 B CN109657527 B CN 109657527B CN 201710947483 A CN201710947483 A CN 201710947483A CN 109657527 B CN109657527 B CN 109657527B
- Authority
- CN
- China
- Prior art keywords
- identification
- artist
- pen
- database
- identifying
- 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
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/80—Recognising image objects characterised by unique random patterns
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/95—Pattern authentication; Markers therefor; Forgery detection
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a painting brush stroke identification system and a method, wherein the painting brush stroke identification system comprises the following components: the artist skill feature library construction module and the identification module; the artist skill feature library construction module is used for constructing an artist skill feature database for a large number of different artist genuine works; obtaining a work image, carrying out classification recognition, detail splitting and operation characteristic value conversion, and comprehensively forming an artist technical characteristic database to provide a reference basis for identifying and recognizing painting works; the identification module is used for comparing the obtained data with the data in the artist technical feature library through identification, refinement and splitting and calculation of the operation feature value of the identified artwork image, so as to judge the author of the identified artwork. The drawing stroke identification system and the drawing stroke identification method can improve the identification efficiency and accuracy, can feed back the true degree percentage of each element of the identified artwork, and provide a reference basis for identification.
Description
Technical Field
The invention belongs to the technical field of painting identification, relates to a painting identification system, and particularly relates to a painting brush touch identification system; meanwhile, the invention also relates to a painting brush touch identification method.
Background
Painting and calligraphy identification is an identification mode of folk painting and calligraphy works. The existing identification mode is generally identified by corresponding experts through subjective knowledge, has strong subjectivity, is easy to deviate, and influences the accuracy of identification; in addition, since the conventional authentication method takes a long time, the user needs to store the painting and calligraphy works for a long time at the authentication person, and the user of the painting and calligraphy works is not careful.
In view of this, there is an urgent need to design a painting and calligraphy identification method so as to overcome the above-mentioned drawbacks of the existing painting and calligraphy identification method.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: the drawing pen touch identification system can improve the identification efficiency and accuracy, and can feed back the true degree percentage of each element of the identified artwork and provide a reference basis for identification.
In addition, the invention also provides a painting brush touch identification method, which can improve the identification efficiency and accuracy, and can feed back the true degree percentage of each element of the identified artwork and provide a reference basis for identification.
In order to solve the technical problems, the invention adopts the following technical scheme:
a brush stroke identification system, the brush stroke identification system comprising:
The artist skill feature library construction module is used for constructing an artist skill feature database for a large number of different artist genuine works; obtaining a work image, carrying out classification identification, detail splitting and operation characteristic value conversion, and simultaneously classifying and defining data of part of artist works through reliable art appreciation materials to comprehensively form an artist skill characteristic database constructed by a unified algorithm, so as to provide a reference basis for identifying and identifying painting art works;
the identification module is used for comprehensively comparing the requirement of the combination part manual setting with the similarity of the common artist sample and the element sample manipulation feature value in the artist manipulation feature database after the identified artwork image is identified, thinned, split and calculated by the basic calculation of the feature value, and comprehensively identifying the artwork as the similarity percentage of the corresponding author from the angles of common skills and paintings and penmanship habits; listing the similarity percentage of each drawing element of the identification work as the identification result output;
the artist technique feature library self-learning updating module is used for improving the database by increasing the true trace amount of the painting artwork and the fake painting amount with reference value continuously, so that the accuracy of a judging algorithm is improved;
The artist skill feature library construction module comprises a drawing image acquisition unit, a classification and identification unit, a refinement and splitting unit, an operation feature value conversion unit and an artist skill feature database;
a drawing image acquisition unit for acquiring image data of each artist's drawings;
the classification and identification unit is used for identifying and classifying the image information of the works according to various elements in the genuine drawing images of the artists, and identifying and distinguishing each identification element and the information collection block;
the refining and splitting unit is used for refining and splitting each identification element into finer identification areas;
the operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating and pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work;
the artist skill characteristic database is used for storing the data of the corresponding identification elements of each artist for the subsequent comparison and identification of the comparison and identification unit;
the identification module comprises a drawing image acquisition unit, a classification identification unit, a refinement splitting unit, an operation characteristic value conversion unit and a comparison identification unit;
A drawing image acquisition unit for acquiring image data of the identified drawing;
the classification and identification unit is used for carrying out identification and classification on the image information of the works according to various elements in the painting image, and identifying and distinguishing each identification element and the information collection block;
the refining and splitting unit is used for refining and splitting each identification element into finer identification areas;
the operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating and pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work;
the comparison and identification unit is used for comparing each characteristic value of the identified painting with each corresponding characteristic value in the artist technical characteristic database, and judging that the painting is the painting of the corresponding artist if the comparison value is in a set threshold range; otherwise, it is determined that the drawing is not the corresponding artist and a corresponding similarity percentage is provided.
The comparison and identification unit comprises a basic identification unit, a pen touch technique identification unit and a fuzzy identification unit;
the basic identification unit is used for carrying out comprehensive comparison on the similarity of the identified artwork image and the technical characteristic value of the co-worker sample and the element sample in the artist technical characteristic database by combining part manual setting requirements after carrying out basic calculation of identification, refinement and splitting and operation characteristic values, and comprehensively identifying the artwork as the similarity percentage of the corresponding author from the angles of common techniques and painting and penmanship habits;
Under the condition that different authors and drawing elements are not in the artist skill characteristic database, the program uses common strokes analyzed by the works of the same authors and drawing types in the database, drawing skills and habit characteristics are comprehensively compared, and the possibility of judging whether the identified works are author true is judged;
if the same author and drawing elements cannot be found, the similarity percentage of each drawing element of the identification works is listed, and the works and the pen touch methods are referred to and output as identification results;
the pen touch technique identification unit is used as the aid of the true work to be included in the database, and after the author, the drawing technique and the pen touch are set, the pen touch technique identification unit identifies the usage percentage of each drawing element of the work by using the techniques and the pen touch, and the usage percentage is used as the drawing habit data record of the author to play a role in improving the accuracy of the identification database; the use degree of a set drawing technique and a pen touch on each drawing element of the work can be directly identified and used as a reference basis for identifying the work;
the fuzzy identification unit is used for comparing the identified artwork image with the actual trace record characteristic values of all the author approximate drawing elements in the artist skill characteristic database after identifying, refining, splitting and calculating the basic calculation of the characteristic values;
The first three authors with the highest similarity and the similarity percentage of each drawing element are listed as the feedback of the identification result feedback identification result, and are used as the reference basis for judging the possibility of the suspected true of the innominate works.
A brush stroke identification system, the brush stroke identification system comprising:
the artist skill feature library construction module is used for constructing an artist skill feature database for a large number of different artist genuine works; obtaining a work image, carrying out classification recognition, detail splitting and operation characteristic value conversion, and comprehensively forming an artist technical characteristic database to provide a reference basis for identifying and recognizing painting works;
the identification module is used for comparing the obtained data with the data in the artist technical feature library through identification, thinning and splitting and calculation of the operation feature value of the identified artwork image, so as to judge the author of the identified artwork.
As a preferable scheme of the invention, the painting brush stroke identification system further comprises an artist technical feature library self-learning updating module, which is used for improving the database by continuously increasing the true trace amount of painting artwork and the fake painting amount with reference value, and improving the accuracy of a judging algorithm.
As a preferable scheme of the invention, the artist skill feature library construction module comprises a drawing image acquisition unit, a classification and identification unit, a refinement and splitting unit, an operation feature value conversion unit and an artist skill feature database;
a drawing image acquisition unit for acquiring image data of each artist's drawings;
the classification and identification unit is used for identifying and classifying the image information of the works according to various elements in the genuine drawing images of the artists, and identifying and distinguishing each identification element and the information collection block;
the refining and splitting unit is used for refining and splitting each identification element into finer identification areas;
the operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating and pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work;
the artist skill characteristic database is used for storing the data of the corresponding identification elements of each artist for the subsequent comparison and identification of the comparison and identification unit.
As a preferable scheme of the invention, the identification module comprises a drawing image acquisition unit, a classification and identification unit, a refinement and splitting unit, an operation characteristic value conversion unit and a comparison and identification unit;
A drawing image acquisition unit for acquiring image data of the identified drawing;
the classification and identification unit is used for carrying out identification and classification on the image information of the works according to various elements in the painting image, and identifying and distinguishing each identification element and the information collection block;
the refining and splitting unit is used for refining and splitting each identification element into finer identification areas;
the operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating and pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work;
the comparison and identification unit is used for comparing each characteristic value of the identified painting with each corresponding characteristic value in the artist technical characteristic database, and judging that the painting is the painting of the corresponding artist if the comparison value is in a set threshold range; otherwise, it is determined that the drawing is not the corresponding artist and a corresponding similarity percentage is provided.
As a preferable mode of the invention, the comparison and identification unit comprises a basic identification unit, a pen touch technique identification unit and a fuzzy identification unit;
The basic identification unit is used for carrying out comprehensive comparison on the similarity of the identified artwork image and the technical characteristic value of the co-worker sample and the element sample in the artist technical characteristic database by combining part manual setting requirements after carrying out basic calculation of identification, refinement and splitting and operation characteristic values, and comprehensively identifying the artwork as the similarity percentage of the corresponding author from the angles of common techniques and painting and penmanship habits;
under the condition that different authors and drawing elements are not in the artist skill characteristic database, the program uses common strokes analyzed by the works of the same authors and drawing types in the database, drawing skills and habit characteristics are comprehensively compared, and the possibility of judging whether the identified works are author true is judged;
if the same author and drawing elements cannot be found, the similarity percentage of each drawing element of the identification works is listed, and the works and the pen touch methods are referred to and output as identification results;
the pen touch technique identification unit is used as the aid of the true work to be included in the database, and after the author, the drawing technique and the pen touch are set, the pen touch technique identification unit identifies the usage percentage of each drawing element of the work by using the techniques and the pen touch, and the usage percentage is used as the drawing habit data record of the author to play a role in improving the accuracy of the identification database; the use degree of a set drawing technique and a pen touch on each drawing element of the work can be directly identified and used as a reference basis for identifying the work;
The fuzzy identification unit is used for comparing the identified artwork image with the actual trace record characteristic values of all the author approximate drawing elements in the artist skill characteristic database after identifying, refining, splitting and calculating the basic calculation of the characteristic values;
the first three authors with the highest similarity and the similarity percentage of each drawing element are listed as the feedback of the identification result feedback identification result, and are used as the reference basis for judging the possibility of the suspected true of the innominate works.
A brush stroke identification method, the brush stroke identification method comprising:
step S1, an artist skill feature library construction step, wherein an artist skill feature database is built for a large number of different artist genuine works; obtaining a work image, carrying out classification identification, detail splitting and operation characteristic value conversion, and simultaneously classifying and defining data of part of artist works through reliable art appreciation materials to comprehensively form an artist skill characteristic database constructed by a unified algorithm, so as to provide a reference basis for identifying and identifying painting art works;
the step S1 includes:
a drawing image acquisition step of acquiring image data of drawings of each artist;
a classification and identification step, namely identifying and classifying the image information of works according to various elements in the genuine drawing images of each artist, and identifying and distinguishing each identification element and each information collection block;
A refinement and resolution step, namely performing refinement and resolution on each identification element to split the identification element into finer identification areas;
a step of converting operation characteristic values, in which, in each identification element of the work, pen starting, pen driving, pen rotating, pen receiving used by drawing are classified, record is identified and converted into characteristic values which are convenient to store and compare;
an artist skill characteristic database forming step of storing data of corresponding identification elements of each artist for comparison and identification in a subsequent comparison and identification step;
step S2, an identification step, namely after the identified artwork image is identified, thinned and split and the basis of the operation characteristic value is calculated, combining part manual setting requirements and the similarity of the same-composition sample and the element sample technical characteristic value in an artist technical characteristic database are comprehensively compared, and the artwork is comprehensively identified as the similarity percentage of the corresponding author from the aspects of common techniques and painting and penmanship habits; listing the similarity percentage of each drawing element of the identification work as the identification result output;
the step S2 includes:
a drawing image acquisition step of acquiring image data of the identified drawing;
a classification and identification step of identifying and classifying the image information of the works according to various elements in the painting image, and identifying and distinguishing each identification element and the information collection block;
A refinement and resolution step, namely performing refinement and resolution on each identification element to split the identification element into finer identification areas;
a step of converting operation characteristic values, in which, in each identification element of the work, pen starting, pen driving, pen rotating, pen receiving used by drawing are classified, record is identified and converted into characteristic values which are convenient to store and compare;
a comparison and identification step, wherein each characteristic value of the identified drawing is compared with each corresponding characteristic value in the artist technical characteristic database, and if the comparison value is in a set threshold range, the drawing of the corresponding artist is judged; otherwise, it is determined that the drawing is not the corresponding artist and a corresponding similarity percentage is provided.
The comparison and identification step comprises a basic identification process, a pen touch technique identification process and a fuzzy identification process;
in the basic identification process, after the identified artwork image is identified, thinned and split, and the basic calculation of the operation characteristic value is carried out, the combination part is manually set to require comprehensive comparison with the similarity of the co-worker sample and the element sample technical characteristic value in the artist technical characteristic database, and the artwork is comprehensively identified as the similarity percentage of the corresponding author from the angles of common technique and drawing and pen habit;
Under the condition that different authors and drawing elements are not in the artist skill characteristic database, the program uses common strokes analyzed by the works of the same authors and drawing types in the database, drawing skills and habit characteristics are comprehensively compared, and the possibility of judging whether the identified works are author true is judged;
if the same author and drawing elements cannot be found, the similarity percentage of each drawing element of the identification works is listed, and the works and the pen touch methods are referred to and output as identification results;
in the process of identifying the pen touch technique, the pen touch technique is used as the assistance of the true work to be included in the database, and after the author, the drawing technique and the pen touch are set, the pen touch technique identifying unit identifies the usage percentage of each drawing element of the work by using the techniques and the pen touch, and the usage percentage is used as the drawing habit data record of the author to play a role in improving the accuracy of the identification database; the use degree of a set drawing technique and a pen touch on each drawing element of the work can be directly identified and used as a reference basis for identifying the work;
in the fuzzy identification process, the identified artwork image is compared with the true record characteristic values of all author approximate drawing elements in an artist technical characteristic database after basic calculation of identification, refinement and splitting and operation characteristic values; the first three authors with the highest similarity and the similarity percentage of each drawing element are listed as identification result feedback, and the identification result feedback is used as a reference basis for judging the possibility of the suspected true of the innominate works;
Step S3, a self-learning updating step of an artist technique feature library is carried out, so that the database is perfected by increasing the true trace amount of painting artwork and the fake painting amount with reference value, and the accuracy of a judging algorithm is improved;
a brush stroke identification method, the brush stroke identification method comprising:
an artist skill feature library construction step of constructing an artist skill feature database by creating a large number of different artist trace works; obtaining a work image, carrying out classification recognition, detail splitting and operation characteristic value conversion, and comprehensively forming an artist technical characteristic database to provide a reference basis for identifying and recognizing painting works;
and the identification step is to identify, refine and split the identified artwork image, calculate the characteristic value, and compare the obtained data with the data in the artist technical characteristic library so as to judge the author of the identified artwork.
As a preferable scheme of the invention, the painting brush touch identification method further comprises a self-learning updating step of an artist technical feature library, so that the database is perfected by increasing the true trace amount of painting artwork and the fake painting amount with reference value, and the accuracy of a judging algorithm is improved.
As a preferred embodiment of the present invention, the step S1 includes:
a drawing image acquisition step of acquiring image data of drawings of each artist;
a classification and identification step, namely identifying and classifying the image information of works according to various elements in the genuine drawing images of each artist, and identifying and distinguishing each identification element and each information collection block;
a refinement and resolution step, namely performing refinement and resolution on each identification element to split the identification element into finer identification areas;
a step of converting operation characteristic values, in which, in each identification element of the work, pen starting, pen driving, pen rotating, pen receiving used by drawing are classified, record is identified and converted into characteristic values which are convenient to store and compare;
an artist skill characteristic database forming step of storing data of corresponding identification elements of each artist for comparison and identification in a subsequent comparison and identification step;
the step S2 includes:
a drawing image acquisition step of acquiring image data of the identified drawing;
a classification and identification step of identifying and classifying the image information of the works according to various elements in the painting image, and identifying and distinguishing each identification element and the information collection block;
A refinement and resolution step, namely performing refinement and resolution on each identification element to split the identification element into finer identification areas;
a step of converting operation characteristic values, in which, in each identification element of the work, pen starting, pen driving, pen rotating, pen receiving used by drawing are classified, record is identified and converted into characteristic values which are convenient to store and compare;
a comparison and identification step, wherein each characteristic value of the identified drawing is compared with each corresponding characteristic value in the artist technical characteristic database, and if the comparison value is in a set threshold range, the drawing of the corresponding artist is judged; otherwise, it is determined that the drawing is not the corresponding artist and a corresponding similarity percentage is provided.
The invention has the beneficial effects that: the drawing stroke identification system and the drawing stroke identification method can improve the identification efficiency and accuracy, can feed back the true degree percentage of each element of the identified artwork, and provide a reference basis for identification.
Drawings
FIG. 1 is a schematic diagram of the composition of the brush stroke identification system of the present invention.
FIG. 2 is a flow chart of a method for identifying brush strokes according to the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Example 1
Referring to FIG. 1, the present invention discloses a painting brush stroke identification system, comprising: artist skill feature library construction module 1, authentication module 2, artist skill feature library self-learning update module 3.
The artist skill feature library construction module is used for constructing an artist skill feature database for a large number of different artist genuine works; and obtaining the image of the work, carrying out classification identification, detail splitting and operation characteristic value conversion, and simultaneously classifying and defining data of part of artists through reliable artistic appreciation materials to comprehensively form an artist technical characteristic database constructed by a unified algorithm, so as to provide a reference basis for identifying and identifying the painting artists.
The identification module is used for comprehensively comparing the requirement of the combination part manual setting with the similarity of the common artist sample and the element sample manipulation feature value in the artist manipulation feature database after the identified artwork image is identified, thinned, split and calculated by the basic calculation of the feature value, and comprehensively identifying the artwork as the similarity percentage of the corresponding author from the angles of common skills and paintings and penmanship habits; and (5) listing the similarity percentage of each drawing element of the identification work as the identification result output.
The artist technique feature library self-learning updating module is used for improving the database by increasing the true trace amount of the painting artwork and the fake painting amount with reference value continuously, and improving the accuracy of the judging algorithm.
The artist skill feature library construction module comprises a drawing image acquisition unit, a classification and identification unit, a refinement and splitting unit, an operation feature value conversion unit and an artist skill feature database.
A drawing image acquisition unit for acquiring image data of each artist's drawings;
the classification and identification unit is used for carrying out identification and classification on the image information of the works according to various elements in the images of the true drawings of the artists, and identifying and distinguishing each identification element and the information collection block.
And the refinement and resolution unit is used for refining and resolving each identification element into finer identification areas.
The operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating, pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work.
The artist skill characteristic database is used for storing the data of the corresponding identification elements of each artist for the subsequent comparison and identification of the comparison and identification unit.
The identification module comprises a drawing image acquisition unit, a classification identification unit, a refinement splitting unit, an operation characteristic value conversion unit and a comparison identification unit.
And the drawing image acquisition unit is used for acquiring the image data of the identified drawing.
The classification and identification unit is used for carrying out identification and classification on the image information of the works according to various elements in the painting image, and identifying and distinguishing each identification element and the information collection block.
And the refinement and resolution unit is used for refining and resolving each identification element into finer identification areas.
The operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating, pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work.
The comparison and identification unit is used for comparing each characteristic value of the identified painting with each corresponding characteristic value in the artist technical characteristic database, and judging that the painting is the painting of the corresponding artist if the comparison value is in a set threshold range; otherwise, it is determined that the drawing is not the corresponding artist and a corresponding similarity percentage is provided.
The comparison and identification unit comprises a basic identification unit, a pen touch technique identification unit and a fuzzy identification unit.
The basic identification unit is used for carrying out comprehensive comparison on the similarity of the identified artwork image and the skill characteristic value of the co-worker sample and the element sample in the artist skill characteristic database by combining part manual setting requirements after carrying out basic calculation of identification, refinement and splitting and operation characteristic values, and comprehensively identifying the artwork as the similarity percentage of the corresponding author from the angles of common skill and drawing and penmanship habit.
Under the condition that different authors and drawing elements are not in the artist skill characteristic database, the program uses common strokes analyzed by the works of the same authors and drawing types in the database, drawing skills and habit characteristics are comprehensively compared, and the possibility of judging whether the identified works are author true is judged.
If the same author and drawing elements cannot be found, the similarity percentage of each drawing element of the identification works is listed, and the works and the pen touch method are referred to and output as identification results.
The pen touch technique identification unit is used as the aid of the true work to be included in the database, and after the author, the drawing technique and the pen touch are set, the pen touch technique identification unit identifies the usage percentage of each drawing element of the work by using the techniques and the pen touch, and the usage percentage is used as the drawing habit data record of the author to play a role in improving the accuracy of the identification database; the method can directly identify the usage degree of the set drawing technique and pen touch on each drawing element of the work as the reference basis of the identification work.
The fuzzy identification unit is used for comparing the identified artwork image with the actual trace record characteristic values of all the author approximate drawing elements in the artist skill characteristic database after identifying, refining, splitting and calculating the basis of the characteristic values.
The first three authors with the highest similarity and the similarity percentage of each drawing element are listed as the feedback of the identification result feedback identification result, and are used as the reference basis for judging the possibility of the suspected true of the innominate works.
Referring to fig. 2, the invention further discloses a method for identifying the brush strokes, which comprises the following steps:
step S1, an artist skill feature library construction step, wherein an artist skill feature database is built for a large number of different artist genuine works; obtaining a work image, carrying out classification identification, detail splitting and operation characteristic value conversion, and simultaneously classifying and defining data of part of artist works through reliable art appreciation materials to comprehensively form an artist skill characteristic database constructed by a unified algorithm, so as to provide a reference basis for identifying and identifying painting art works;
the step S1 includes:
a drawing image acquisition step of acquiring image data of drawings of each artist;
A classification and identification step, namely identifying and classifying the image information of works according to various elements in the genuine drawing images of each artist, and identifying and distinguishing each identification element and each information collection block;
a refinement and resolution step, namely performing refinement and resolution on each identification element to split the identification element into finer identification areas;
a step of converting operation characteristic values, in which, in each identification element of the work, pen starting, pen driving, pen rotating, pen receiving used by drawing are classified, record is identified and converted into characteristic values which are convenient to store and compare;
an artist skill characteristic database forming step of storing data of corresponding identification elements of each artist for comparison and identification in a subsequent comparison and identification step;
step S2, the identification step is carried out, after the identified artwork image is identified, thinned and split, the basic calculation of the operation characteristic value is carried out, the combination part is manually set to require comprehensive comparison with the similarity of the same-composition sample and the element sample manipulation characteristic value in the artist manipulation characteristic database, and the artwork is comprehensively identified as the similarity percentage of the corresponding author from the aspects of common technique and drawing and penmanship habit; listing the similarity percentage of each drawing element of the identification work as the identification result output;
The step S2 includes:
a drawing image acquisition step of acquiring image data of the identified drawing;
a classification and identification step of identifying and classifying the image information of the works according to various elements in the painting image, and identifying and distinguishing each identification element and the information collection block;
a refinement and resolution step, namely performing refinement and resolution on each identification element to split the identification element into finer identification areas;
a step of converting operation characteristic values, in which, in each identification element of the work, pen starting, pen driving, pen rotating, pen receiving used by drawing are classified, record is identified and converted into characteristic values which are convenient to store and compare;
a comparison and identification step, wherein each characteristic value of the identified drawing is compared with each corresponding characteristic value in the artist technical characteristic database, and if the comparison value is in a set threshold range, the drawing of the corresponding artist is judged; otherwise, it is determined that the drawing is not the corresponding artist and a corresponding similarity percentage is provided.
The comparison and identification step comprises a basic identification process, a pen touch technique identification process and a fuzzy identification process;
in the basic identification process, after the identified artwork image is identified, thinned and split, and the basic calculation of the operation characteristic value is carried out, the combination part is manually set to require comprehensive comparison with the similarity of the co-worker sample and the element sample technical characteristic value in the artist technical characteristic database, and the artwork is comprehensively identified as the similarity percentage of the corresponding author from the angles of common technique and drawing and pen habit;
Under the condition that different authors and drawing elements are not in the artist skill characteristic database, the program uses common strokes analyzed by the works of the same authors and drawing types in the database, drawing skills and habit characteristics are comprehensively compared, and the possibility of judging whether the identified works are author true is judged;
if the same author and drawing elements cannot be found, the similarity percentage of each drawing element of the identification works is listed, and the works and the pen touch methods are referred to and output as identification results;
in the process of identifying the pen touch technique, the pen touch technique is used as the assistance of the true work to be included in the database, and after the author, the drawing technique and the pen touch are set, the pen touch technique identifying unit identifies the usage percentage of each drawing element of the work by using the techniques and the pen touch, and the usage percentage is used as the drawing habit data record of the author to play a role in improving the accuracy of the identification database; the use degree of a set drawing technique and a pen touch on each drawing element of the work can be directly identified and used as a reference basis for identifying the work;
in the fuzzy identification process, the identified artwork image is compared with the true record characteristic values of all author approximate drawing elements in an artist technical characteristic database after basic calculation of identification, refinement and splitting and operation characteristic values; the first three authors with the highest similarity and the similarity percentage of each drawing element are listed as identification result feedback, and the identification result feedback is used as a reference basis for judging the possibility of the suspected true of the innominate works;
Step S3, a self-learning updating step of an artist skill feature library is carried out, so that the true trace amount of painting artwork and the fake painting amount with reference value are continuously increased to perfect a database, and the accuracy of a judging algorithm is improved;
example two
A painting brush stroke identification system is disclosed, the painting brush stroke identification system comprising: the artist skill feature library construction module and the identification module.
The artist skill feature library construction module is used for constructing an artist skill feature database for a large number of different artist genuine works; and obtaining a work image, carrying out classification identification, detail splitting and operation characteristic value conversion, and comprehensively forming an artist technical characteristic database to provide a reference basis for identifying and identifying painting works of art.
The identification module is used for comparing the obtained data with the data in the artist technical feature library through identification, thinning and splitting and calculation of the operation feature value of the identified artwork image, so as to judge the author of the identified artwork.
The invention also discloses a painting brush stroke identification method, which comprises the following steps:
an artist skill feature library construction step of constructing an artist skill feature database by creating a large number of different artist trace works; obtaining a work image, carrying out classification recognition, detail splitting and operation characteristic value conversion, and comprehensively forming an artist technical characteristic database to provide a reference basis for identifying and recognizing painting works;
And a step of identifying the module, namely identifying, refining and splitting the identified artwork image, calculating the characteristic value, and comparing the obtained data with the data in the artist technical characteristic library so as to judge the author of the identified artwork.
In summary, the system and the method for identifying the painting brush strokes provided by the invention can improve the efficiency and the accuracy of identification, can feed back the percentage of the degree of authenticity of each element of the identified artwork, and provide a reference basis for identification.
The description and applications of the present invention herein are illustrative and are not intended to limit the scope of the invention to the embodiments described above. Variations and modifications of the embodiments disclosed herein are possible, and alternatives and equivalents of the various components of the embodiments are known to those of ordinary skill in the art. It will be clear to those skilled in the art that the present invention may be embodied in other forms, structures, arrangements, proportions, and with other assemblies, materials, and components, without departing from the spirit or essential characteristics thereof. Other variations and modifications of the embodiments disclosed herein may be made without departing from the scope and spirit of the invention.
Claims (5)
1. A painting brush stroke identification system, the painting brush stroke identification system comprising:
the artist skill feature library construction module is used for constructing an artist skill feature database for a large number of different artist genuine works; obtaining a work image, carrying out classification identification, detail splitting and operation characteristic value conversion, and simultaneously classifying and defining data of part of artist works through reliable art appreciation materials to comprehensively form an artist skill characteristic database constructed by a unified algorithm, so as to provide a reference basis for identifying and identifying painting art works;
the identification module is used for comprehensively comparing the requirement of the combination part manual setting with the similarity of the common artist sample and the element sample manipulation feature value in the artist manipulation feature database after the identified artwork image is identified, thinned, split and calculated by the basic calculation of the feature value, and comprehensively identifying the artwork as the similarity percentage of the corresponding author from the angles of common skills and paintings and penmanship habits; listing the similarity percentage of each drawing element of the identification work as the identification result output;
the artist technique feature library self-learning updating module is used for improving the database by increasing the true trace amount of the painting artwork and the fake painting amount with reference value continuously, so that the accuracy of a judging algorithm is improved;
The artist skill feature library construction module comprises a drawing image acquisition unit, a classification and identification unit, a refinement and splitting unit, an operation feature value conversion unit and an artist skill feature database;
a drawing image acquisition unit for acquiring image data of each artist's drawings;
the classification and identification unit is used for identifying and classifying the image information of the works according to various elements in the genuine drawing images of the artists, and identifying and distinguishing each identification element and the information collection block;
the refining and splitting unit is used for refining and splitting each identification element into finer identification areas;
the operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating and pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work;
the artist skill characteristic database is used for storing the data of the corresponding identification elements of each artist for the subsequent comparison and identification of the comparison and identification unit;
the identification module comprises a drawing image acquisition unit, a classification identification unit, a refinement splitting unit, an operation characteristic value conversion unit and a comparison identification unit;
A drawing image acquisition unit for acquiring image data of the identified drawing;
the classification and identification unit is used for carrying out identification and classification on the image information of the works according to various elements in the painting image, and identifying and distinguishing each identification element and the information collection block;
the refining and splitting unit is used for refining and splitting each identification element into finer identification areas;
the operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating and pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work;
the comparison and identification unit is used for comparing each characteristic value of the identified painting with each corresponding characteristic value in the artist technical characteristic database, and judging that the painting is the painting of the corresponding artist if the comparison value is in a set threshold range; otherwise, judging that the drawing is not the drawing of the corresponding artist, and providing a corresponding similarity percentage;
the comparison and identification unit comprises a basic identification unit, a pen touch technique identification unit and a fuzzy identification unit;
the basic identification unit is used for carrying out comprehensive comparison on the similarity of the identified artwork image and the technical characteristic value of the co-worker sample and the element sample in the artist technical characteristic database by combining part manual setting requirements after carrying out basic calculation of identification, refinement and splitting and operation characteristic values, and comprehensively identifying the artwork as the similarity percentage of the corresponding author from the angles of common techniques and painting and penmanship habits;
Under the condition that different authors and drawing elements are not in the artist skill characteristic database, the program uses common strokes analyzed by the works of the same authors and drawing types in the database, drawing skills and habit characteristics are comprehensively compared, and the possibility of judging whether the identified works are author true is judged;
if the same author and drawing elements cannot be found, the similarity percentage of each drawing element of the identification works is listed, and the works and the pen touch methods are referred to and output as identification results;
the pen touch technique identification unit is used as the aid of the true work to be included in the database, and after the author, the drawing technique and the pen touch are set, the pen touch technique identification unit identifies the usage percentage of each drawing element of the work by using the techniques and the pen touch, and the usage percentage is used as the drawing habit data record of the author to play a role in improving the accuracy of the identification database; the use degree of a set drawing technique and a pen touch on each drawing element of the work can be directly identified and used as a reference basis for identifying the work;
the fuzzy identification unit is used for comparing the identified artwork image with the actual trace record characteristic values of all the author approximate drawing elements in the artist skill characteristic database after identifying, refining, splitting and calculating the basic calculation of the characteristic values;
The first three authors with the highest similarity and the similarity percentage of each drawing element are listed as the feedback of the identification result feedback identification result, and are used as the reference basis for judging the possibility of the suspected true of the innominate works.
2. A painting brush stroke identification system, the painting brush stroke identification system comprising:
the artist skill feature library construction module is used for constructing an artist skill feature database for a large number of different artist genuine works; obtaining a work image, carrying out classification recognition, detail splitting and operation characteristic value conversion, and comprehensively forming an artist technical characteristic database to provide a reference basis for identifying and recognizing painting works;
the identification module is used for comparing the obtained data with the data in the artist technical feature library through identification, thinning and splitting and calculation of the operation feature value of the identified artwork image so as to judge the author of the identified artwork;
the identification module comprises a drawing image acquisition unit, a classification identification unit, a refinement splitting unit, an operation characteristic value conversion unit and a comparison identification unit;
a drawing image acquisition unit for acquiring image data of the identified drawing;
The classification and identification unit is used for carrying out identification and classification on the image information of the works according to various elements in the painting image, and identifying and distinguishing each identification element and the information collection block;
the refining and splitting unit is used for refining and splitting each identification element into finer identification areas;
the operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating and pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work;
the comparison and identification unit is used for comparing each characteristic value of the identified painting with each corresponding characteristic value in the artist technical characteristic database, and judging that the painting is the painting of the corresponding artist if the comparison value is in a set threshold range; otherwise, judging that the drawing is not the drawing of the corresponding artist, and providing a corresponding similarity percentage;
the comparison and identification unit comprises a basic identification unit, a pen touch technique identification unit and a fuzzy identification unit;
the basic identification unit is used for carrying out comprehensive comparison on the similarity of the identified artwork image and the technical characteristic value of the co-worker sample and the element sample in the artist technical characteristic database by combining part manual setting requirements after carrying out basic calculation of identification, refinement and splitting and operation characteristic values, and comprehensively identifying the artwork as the similarity percentage of the corresponding author from the angles of common techniques and painting and penmanship habits;
Under the condition that different authors and drawing elements are not in the artist skill characteristic database, the program uses common strokes analyzed by the works of the same authors and drawing types in the database, drawing skills and habit characteristics are comprehensively compared, and the possibility of judging whether the identified works are author true is judged;
if the same author and drawing elements cannot be found, the similarity percentage of each drawing element of the identification works is listed, and the works and the pen touch methods are referred to and output as identification results;
the pen touch technique identification unit is used as the aid of the true work to be included in the database, and after the author, the drawing technique and the pen touch are set, the pen touch technique identification unit identifies the usage percentage of each drawing element of the work by using the techniques and the pen touch, and the usage percentage is used as the drawing habit data record of the author to play a role in improving the accuracy of the identification database; the use degree of a set drawing technique and a pen touch on each drawing element of the work can be directly identified and used as a reference basis for identifying the work;
the fuzzy identification unit is used for comparing the identified artwork image with the actual trace record characteristic values of all the author approximate drawing elements in the artist skill characteristic database after identifying, refining, splitting and calculating the basic calculation of the characteristic values;
The first three authors with the highest similarity and the similarity percentage of each drawing element are listed as the feedback of the identification result feedback identification result, and are used as the reference basis for judging the possibility of the suspected true of the innominate works.
3. The brush stroke identification system of claim 2, wherein:
the painting brush stroke identification system further comprises an artist technical feature library self-learning updating module which is used for improving the database by increasing the true trace amount of painting artwork and the fake painting amount with reference value continuously, and improving the accuracy of a judging algorithm.
4. The brush stroke identification system of claim 2, wherein:
the artist skill feature library construction module comprises a drawing image acquisition unit, a classification and identification unit, a refinement and splitting unit, an operation feature value conversion unit and an artist skill feature database;
a drawing image acquisition unit for acquiring image data of each artist's drawings;
the classification and identification unit is used for identifying and classifying the image information of the works according to various elements in the genuine drawing images of the artists, and identifying and distinguishing each identification element and the information collection block;
the refining and splitting unit is used for refining and splitting each identification element into finer identification areas;
The operation characteristic value conversion unit is used for classifying, identifying and recording, and finally converting the characteristic values into characteristic values which are convenient to store and compare according to pen starting, pen driving, pen rotating and pen receiving multi-stage and various different technical characteristics of the drawing in each identification element of the work;
the artist skill characteristic database is used for storing the data of the corresponding identification elements of each artist for the subsequent comparison and identification of the comparison and identification unit.
5. A method for identifying brush strokes, the method comprising:
step S1, an artist skill feature library construction step, wherein an artist skill feature database is built for a large number of different artist genuine works; obtaining a work image, carrying out classification identification, detail splitting and operation characteristic value conversion, and simultaneously classifying and defining data of part of artist works through reliable art appreciation materials to comprehensively form an artist skill characteristic database constructed by a unified algorithm, so as to provide a reference basis for identifying and identifying painting art works;
the step S1 includes:
a drawing image acquisition step of acquiring image data of drawings of each artist;
a classification and identification step, namely identifying and classifying the image information of works according to various elements in the genuine drawing images of each artist, and identifying and distinguishing each identification element and each information collection block;
A refinement and resolution step, namely performing refinement and resolution on each identification element to split the identification element into finer identification areas;
a step of converting operation characteristic values, in which, in each identification element of the work, pen starting, pen driving, pen rotating, pen receiving used by drawing are classified, record is identified and converted into characteristic values which are convenient to store and compare;
an artist skill characteristic database forming step of storing data of corresponding identification elements of each artist for comparison and identification in a subsequent comparison and identification step;
step S2, an identification step, namely after the identified artwork image is identified, thinned and split and the basis of the operation characteristic value is calculated, combining part manual setting requirements and the similarity of the same-composition sample and the element sample technical characteristic value in an artist technical characteristic database are comprehensively compared, and the artwork is comprehensively identified as the similarity percentage of the corresponding author from the aspects of common techniques and painting and penmanship habits; listing the similarity percentage of each drawing element of the identification work as the identification result output;
the step S2 includes:
a drawing image acquisition step of acquiring image data of the identified drawing;
a classification and identification step of identifying and classifying the image information of the works according to various elements in the painting image, and identifying and distinguishing each identification element and the information collection block;
A refinement and resolution step, namely performing refinement and resolution on each identification element to split the identification element into finer identification areas;
a step of converting operation characteristic values, in which, in each identification element of the work, pen starting, pen driving, pen rotating, pen receiving used by drawing are classified, record is identified and converted into characteristic values which are convenient to store and compare;
a comparison and identification step, wherein each characteristic value of the identified drawing is compared with each corresponding characteristic value in the artist technical characteristic database, and if the comparison value is in a set threshold range, the drawing of the corresponding artist is judged; otherwise, judging that the drawing is not the drawing of the corresponding artist, and providing a corresponding similarity percentage;
the comparison and identification step comprises a basic identification process, a pen touch technique identification process and a fuzzy identification process;
in the basic identification process, after the identified artwork image is identified, thinned and split, and the basic calculation of the operation characteristic value is carried out, the combination part is manually set to require comprehensive comparison with the similarity of the co-worker sample and the element sample technical characteristic value in the artist technical characteristic database, and the artwork is comprehensively identified as the similarity percentage of the corresponding author from the angles of common technique and drawing and pen habit;
Under the condition that different authors and drawing elements are not in the artist skill characteristic database, the program uses common strokes analyzed by the works of the same authors and drawing types in the database, drawing skills and habit characteristics are comprehensively compared, and the possibility of judging whether the identified works are author true is judged;
if the same author and drawing elements cannot be found, the similarity percentage of each drawing element of the identification works is listed, and the works and the pen touch methods are referred to and output as identification results;
in the process of identifying the pen touch technique, the pen touch technique is used as the assistance of the true work to be included in the database, and after the author, the drawing technique and the pen touch are set, the pen touch technique identifying unit identifies the usage percentage of each drawing element of the work by using the techniques and the pen touch, and the usage percentage is used as the drawing habit data record of the author to play a role in improving the accuracy of the identification database; the use degree of a set drawing technique and a pen touch on each drawing element of the work can be directly identified and used as a reference basis for identifying the work;
in the fuzzy identification process, the identified artwork image is compared with the true record characteristic values of all author approximate drawing elements in an artist technical characteristic database after basic calculation of identification, refinement and splitting and operation characteristic values; the first three authors with the highest similarity and the similarity percentage of each drawing element are listed as identification result feedback, and the identification result feedback is used as a reference basis for judging the possibility of the suspected true of the innominate works;
And step S3, a self-learning updating step of an artist technique feature library is carried out, so that the database is perfected by increasing the true trace amount of the painting artwork and the fake painting amount with reference value, and the accuracy of a judging algorithm is improved.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710947483.XA CN109657527B (en) | 2017-10-12 | 2017-10-12 | Painting brush touch identification system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710947483.XA CN109657527B (en) | 2017-10-12 | 2017-10-12 | Painting brush touch identification system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109657527A CN109657527A (en) | 2019-04-19 |
| CN109657527B true CN109657527B (en) | 2023-07-14 |
Family
ID=66109323
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710947483.XA Active CN109657527B (en) | 2017-10-12 | 2017-10-12 | Painting brush touch identification system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109657527B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110458804B (en) * | 2019-07-05 | 2023-03-10 | 国家珠宝玉石首饰检验集团有限公司 | Xinjiang Hetian jade material identification system and method |
| CN112732988A (en) * | 2021-01-12 | 2021-04-30 | 青岛农业大学 | System and method for screening and displaying artwork |
| CN115705688A (en) * | 2021-08-10 | 2023-02-17 | 万维数码智能有限公司 | Ancient and modern artwork identification method and system based on artificial intelligence |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009146272A (en) * | 2007-12-17 | 2009-07-02 | Tadaaki Goto | Old painting and calligraphic work assessing system |
| CN103116755A (en) * | 2013-01-27 | 2013-05-22 | 深圳市书圣艺术品防伪鉴定有限公司 | Automatic painting and calligraphy authenticity degree detecting system and method thereof |
| CN103336942A (en) * | 2013-04-28 | 2013-10-02 | 中山大学 | Traditional Chinese painting identification method based on Radon BEMD (bidimensional empirical mode decomposition) transformation |
| CN106338487A (en) * | 2016-09-29 | 2017-01-18 | 北京建筑大学 | Calligraphy and painting identification method and device |
-
2017
- 2017-10-12 CN CN201710947483.XA patent/CN109657527B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009146272A (en) * | 2007-12-17 | 2009-07-02 | Tadaaki Goto | Old painting and calligraphic work assessing system |
| CN103116755A (en) * | 2013-01-27 | 2013-05-22 | 深圳市书圣艺术品防伪鉴定有限公司 | Automatic painting and calligraphy authenticity degree detecting system and method thereof |
| CN103336942A (en) * | 2013-04-28 | 2013-10-02 | 中山大学 | Traditional Chinese painting identification method based on Radon BEMD (bidimensional empirical mode decomposition) transformation |
| CN106338487A (en) * | 2016-09-29 | 2017-01-18 | 北京建筑大学 | Calligraphy and painting identification method and device |
Non-Patent Citations (1)
| Title |
|---|
| 计算机辅助的国画真伪鉴别研究;关晓惠;潘纲;吴朝晖;吴敢;;计算机应用与软件(第04期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109657527A (en) | 2019-04-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111753767B (en) | Method and device for automatically correcting operation, electronic equipment and storage medium | |
| Quack et al. | Efficient mining of frequent and distinctive feature configurations | |
| CN105046730B (en) | Written handwriting rendering method and device applied to writing brush | |
| CN109657527B (en) | Painting brush touch identification system and method | |
| CN110929760A (en) | Garbage classification software based on computer vision | |
| CN109685052A (en) | Method for processing text images, device, electronic equipment and computer-readable medium | |
| CN110689535B (en) | Workpiece identification method and device, electronic equipment and storage medium | |
| CN1701323A (en) | Digital ink database searching using handwriting feature synthesis | |
| CN105190645B (en) | Previous hand-written example is used for hand-written beautification and other application | |
| CN102663454B (en) | Method and device for evaluating character writing standard degree | |
| CN101169830A (en) | Human face portrait automatic generation method based on embedded type hidden markov model and selective integration | |
| CN101980210A (en) | Marked word classifying and grading method and system | |
| CN108710653B (en) | On-demand method, device and system for reading book | |
| CN104036245B (en) | A kind of biological feather recognition method based on online Feature Points Matching | |
| CN106815253B (en) | Mining method based on mixed data type data | |
| CN109670365B (en) | Handwriting identification system and method | |
| CN110188671B (en) | Method for analyzing handwriting characteristics by using machine learning algorithm | |
| Alpar et al. | Online signature verification by spectrogram analysis | |
| Pradhan et al. | A hand gesture recognition using feature extraction | |
| CN104951811B (en) | Row style line recognition methods and device applied to brush writing | |
| CN101901348B (en) | Normalization based handwriting identifying method and identifying device | |
| CN108921006A (en) | The handwritten signature image true and false identifies method for establishing model and distinguishing method between true and false | |
| Yu et al. | Mental workload classification via online writing features | |
| CN108846386B (en) | Intelligent identification and correction method for hand-drawn pattern | |
| CN109240549B (en) | Calligraphy corrector based on external digital equipment and big data intelligent analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |