CN108427828B - Device for automatically evaluating layout quality and optimizing planar design - Google Patents
Device for automatically evaluating layout quality and optimizing planar design Download PDFInfo
- Publication number
- CN108427828B CN108427828B CN201810124753.1A CN201810124753A CN108427828B CN 108427828 B CN108427828 B CN 108427828B CN 201810124753 A CN201810124753 A CN 201810124753A CN 108427828 B CN108427828 B CN 108427828B
- Authority
- CN
- China
- Prior art keywords
- text
- frame
- calculating
- text box
- design
- 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
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Document Processing Apparatus (AREA)
- Image Analysis (AREA)
Abstract
The invention relates to the technical field of graphic and text planar design, and provides a device for automatically evaluating planar design layout quality and optimization, which can evaluate the quality of a designed finished product, self-help adjust and optimize the designed finished product and improve the quality of the designed finished product.
Description
Technical Field
The invention relates to the technical field of graphic and text planar design, in particular to a device for automatically evaluating the planar design layout quality and optimizing.
Background
As the advertising industry develops, people have more and more demands on the flat design. Despite the advent of many computer aided design tools (e.g., Photoshop, SketchUp, Illustrator, etc.), poster design is greatly facilitated, increasing the efficiency of the design. However, the way of realizing poster design by proprietary graphic design software such as Photoshop and CorelDRAW has high professional requirements, and for most people without plane design theory knowledge and basic aesthetic knowledge, it is still a difficult matter to do professional plane design.
Currently, some self-service flat design software realizes simple graphic and text flat design through limited functions. The self-service plane design method is mainly characterized in that a design template is provided for a user in advance, a user-defined area is reserved at a fixed position of the design template, and the user adds image-text materials in the user-defined area. Although the image-text planar design mode is simple to realize and low in professional requirement and can be suitable for the common masses, the final effect of the image-text planar design is limited by the inherent design template, and moreover, because the system lacks an objective judgment standard for the quality of a final design finished product, the design finished product cannot be effectively adjusted and optimized by self, the quality of the design finished product cannot be effectively improved by self, the personalized design requirement of a user cannot be met to a great extent, and the practicability is low.
Disclosure of Invention
Therefore, in order to solve the above problems, the present invention provides an apparatus for automatically evaluating the quality and optimization of a planar design layout, which is capable of evaluating the quality of a designed finished product, so as to perform self-help adjustment and optimization on the designed finished product, thereby improving the quality of the designed finished product.
In order to realize the technical problem, the solution scheme adopted by the invention is as follows: a device for automatically evaluating the quality and optimization of a planar design layout comprises a design structure analysis module, a grading module and an optimization design module;
the design structure analysis module converts a picture format file of a designed finished product into a structured file, and can obtain a text frame attribute and a background picture attribute of the designed finished product according to the structured file, wherein the text frame attribute comprises the frame size of a text frame and the position of the text frame, and the background picture attribute comprises the size of the background picture and color elements of the background picture;
the scoring module obtains the character frame attribute and the background image attribute through the structured file output by the structure analysis module so as to perform design quality scoring, wherein the design quality scoring comprises alignment feature evaluation on the character frame, regularity feature evaluation on the character frame, balance feature evaluation on the character frame and the image, blank feature evaluation on the poster and overlapping feature evaluation on the character frame and the image;
the optimization design module automatically carries out parameter change operation on each constituent parameter of the text box attribute and the background graph attribute respectively, and marks the planar design layout state obtained after the nth parameter change operation as an environmental state SnAmbient state SnCalculating the environment state S by superposing all the characteristic evaluation scores obtained by the scoring modulenThe environmental score function of (1), (Sn); meanwhile, the optimization design module calculates an action execution probability function P (an) of the nth parameter change operation according to the average distribution probability, wherein P (an) = 1/N, and N represents the total number of parameter change operations; the optimization design module obtains an action expected value E of the nth parameter change operation according to an environment score function R (Sn) and an action execution probability function P (an)n，En= p (an) x R (Sn); said powder isAction expected value E corresponding to each parameter change operation by using design change modulenPerforming accumulation calculation to obtain the maximum expected action value EmaxAnd the action expectation value E is setmaxAnd (4) executing the corresponding parameter change operation on the design finished product to obtain the optimized design finished product.
Further, the alignment characteristics of the text boxes are evaluated to calculate the alignment of all the text boxes; the alignment characteristics for the text box were evaluated as:
calculating 6 dimensional coordinate positions of upper, lower, left, right, horizontal middle points and vertical middle points of each text frame, and marking each text frame as T1， T 2，T 3…T n，T nThe data structure representing the dimension coordinate position of the nth text box and the text box frame is represented as Tn{ T n(up), T n(down), T n(left), T n(right), T n(horizion), T n(veritical) }；
Respectively calculating histograms of 6 dimensional coordinate positions, and calculating an average value M of the 6 dimensional coordinate positions:
Mup = (T 1(up) + T 2(up) +…+ T n(up))/2；
Mdown= (T 1(down) + T 2(down) + … + T n(down))/2；
M left = (T 1(left)+ T 2(left)+ … + T n(left) )/2；
M right = (T 1(lright)+ T 2(lright)+ … + T n(lright) )/2；
M horizion = (T 1(horizion)+ T 2(horizion)+ … + T n(horizion) )/2；
M veritical = (T 1(veritical) + T 2(veritical) + … + T n(veritical) )/2；
calculating the dispersion degree D of the 6 dimensional coordinate positions according to the histograms of the 6 dimensional coordinate positions, wherein the dispersion degree is an alignment score;
selecting one dimension with the lowest discrete degree in the 6 dimensional coordinate positions as one alignment mode, and selecting the discrete degree fraction of the alignment mode as the final alignment fraction SAlignment ofI.e. by
SAlignment of= min(Dup, Ddown, Dleft, Dright, Dhorizion, Dvertical )。
Further, the regularity characteristics of the text boxes are evaluated to calculate the width or height consistency of each text box frame; the regularity characteristics for the text box were evaluated as:
firstly, obtaining the width and height data of each text frame, marking each text frame as T1， T 2，T 3…T n，T nRepresenting the nth text box, the dimensional coordinate position data structure of the text box frame being represented as Tn{ T n(width), T n(hight) }；
Calculating the average value M of the width and height data of each text frame:
Mwidth = （T 1（width） + T2(width)+ …+ T n(width)）/3；
Mhight = （T 1(hight)+ T 2(hight) +…+ T n(hight) /3；
calculating the variance of the width and height data of each text frame:
selecting the minimum variance D of the two variancesmin = min(Dwidth，Dhight)；
Fifthly, carrying out normalization calculation on the minimum variance to obtain a regularity score SNormalization= 1/(1+Dmin)。
Further, the balance characteristics of the text box and the picture are evaluated to calculate the upper-lower and left-right symmetry of the visual saliency map; the balance characteristics for the text box and the picture are evaluated as:
setting the importance of the text frame as 1, setting the importance of the background picture as an interval of 0-1, calculating a total graph after all the picture layers are superposed, and calculating a significance graph of the total graph:
marking n character frames as T 1，T 2，T 3…T n， T1 =1, T2 =1, … Tn= 1; marking m background pictures as P respectively1， P2，P3…Pm， P1 = random(0,1) = P2 = P3 = … = Pm；
② calculating the significance T of the text boxsalAnd background Picture saliency Psal：
thirdly, the significance P of the background picture obtained by calculationsalSignificance with text box TsalOverlapping to obtain a final significance map Pfianl，I.e. Pfianl= Psal+Tsal；
Fourthly, calculating a final significance map PfianlTo obtain a balance score SBalancing：
Where m is the total number of background pictures,
representing the significance of the left position of the kth significance map,
representing the significance of the left position of the kth significance map,
showing the significance of the upper edge position of the kth significance map,
the saliency at the bottom position of the kth saliency map is shown.
Further, the blank characteristics of the poster are evaluated as the size of the poster area occupied by the text box and the picture saliency block, and the blank characteristics of the poster are evaluated as follows:
calculating the blank proportion P of the blank of the poster contentwhite：
Area(T)kArea of the K-th character frame, area (P)kArea of the K background picture, area (total) of the design finished product;
normalizing the blank ratio to obtain a blank characteristic evaluation score SWhite space：
Further, the overlapping characteristics of the text box and the picture are evaluated as:
calculating a total graph of all background pictures in the poster after being superposed according to the layers, and calculating a saliency map of the background pictures:
Area(P)kthe area of the K background picture is shown, and m represents the total number of the background pictures;
calculating the shielding proportion:
wherein the content of the first and second substances,
the image area of the superposition position of the image area and the character area is represented;
thirdly, normalization processing is carried out on the shielding proportion, and after normalization processing, the characteristic score S is overlappedOverlap：
By adopting the technical scheme, the invention has the beneficial effects that: the device for automatically evaluating the layout quality and optimization of the planar design can convert aesthetic subjective standards of the design into measurable mathematical evaluation comparison, and further optimize a designed finished product through deep reinforcement learning according to the evaluation, thereby realizing self-help adjustment and optimization of the designed finished product and improving the quality of the designed finished product.
Drawings
FIG. 1 is a block diagram of the structural principles of an embodiment of the present invention.
Detailed Description
The invention will now be further described with reference to the accompanying drawings and specific embodiments.
Referring to fig. 1, an apparatus for automatically evaluating the quality and optimization of a planar design layout according to an embodiment of the present invention includes a design structure analysis module, a scoring module, and an optimization design module.
The design structure analysis module converts a picture format file of a designed finished product into a structured file, and can obtain a text frame attribute and a background picture attribute of the designed finished product according to the structured file, wherein the text frame attribute comprises the frame size of a text frame and the position of the text frame, and the background picture attribute comprises the size of the background picture and color elements of the background picture.
The scoring module obtains the character frame attribute and the background image attribute through the structured file output by the structure analysis module so as to carry out design quality scoring, wherein the design quality scoring comprises alignment feature evaluation on the character frame, regularity feature evaluation on the character frame, balance feature evaluation on the character frame and the image, blank feature evaluation on the poster, and overlapping feature evaluation on the character frame and the image:
evaluating the alignment characteristics of the text boxes to calculate the alignment of all the text boxes; the alignment characteristics for the text box were evaluated as:
calculatingMarking each text box as T according to 6 dimensional coordinate positions of the frame of each text box, namely, the upper, lower, left, right, horizontal middle point and vertical middle point1， T 2，T 3…T n，T nThe data structure representing the dimension coordinate position of the nth text box and the text box frame is represented as Tn{ T n(up), T n(down), T n(left), T n(right), T n(horizion), T n(veritical) }；
Respectively calculating histograms of 6 dimensional coordinate positions, and calculating an average value M of the 6 dimensional coordinate positions:
Mup = (T 1(up) + T 2(up) +…+ T n(up))/2；
Mdown= (T 1(down) + T 2(down) + … + T n(down))/2；
M left = (T 1(left)+ T 2(left)+ … + T n(left) )/2；
M right = (T 1(lright)+ T 2(lright)+ … + T n(lright) )/2；
M horizion = (T 1(horizion)+ T 2(horizion)+ … + T n(horizion) )/2；
M veritical = (T 1(veritical) + T 2(veritical) + … + T n(veritical) )/2；
calculating the dispersion degree D of the 6 dimensional coordinate positions according to the histograms of the 6 dimensional coordinate positions, wherein the dispersion degree is an alignment score;
selecting one dimension with the lowest discrete degree in the 6 dimensional coordinate positions as one alignment mode, and selecting the discrete degree fraction of the alignment mode as the final alignment fraction SAlignment ofI.e. by
SAlignment of= min(Dup, Ddown, Dleft, Dright, Dhorizion, Dvertical )。
Evaluating the regularity characteristics of the text boxes to calculate the width or height consistency of each text box frame; the regularity characteristics for the text box were evaluated as:
firstly, obtaining the width and height data of each text frame, marking each text frame as T1， T 2，T 3…T n，T nRepresenting the nth text box, the dimensional coordinate position data structure of the text box frame being represented as Tn{ T n(width), T n(hight) }；
Calculating the average value M of the width and height data of each text frame:
Mwidth = （T 1（width） + T2(width)+ …+ T n(width)）/3；
Mhight = （T 1(hight)+ T 2(hight) +…+ T n(hight) /3；
calculating the variance of the width and height data of each text frame:
selecting the minimum variance D of the two variancesmin = min(Dwidth，Dhight)；
Fifthly, carrying out normalization calculation on the minimum variance to obtain a regularity score SNormalization= 1/(1+Dmin)。
Evaluating the balance characteristics of the text box and the picture to calculate the upper-lower symmetry and the left-right symmetry of the visual saliency map; the balance characteristics for the text box and the picture are evaluated as:
setting the importance of the text frame as 1, setting the importance of the background picture as an interval of 0-1, calculating a total graph after all the picture layers are superposed, and calculating a significance graph of the total graph:
marking n character frames as T 1，T 2，T 3…T n， T1 =1, T2 =1, … Tn= 1; marking m background pictures as P respectively1， P2，P3…Pm， P1 = random(0,1) = P2 = P3 = … = Pm；
② calculating the significance T of the text boxsalAnd background Picture saliency Psal：
③ general meterCalculated background picture saliency PsalSignificance with text box TsalOverlapping to obtain a final significance map Pfianl，I.e. Pfianl= Psal+Tsal；
Fourthly, calculating a final significance map PfianlTo obtain a balance score SBalancing：
Where m is the total number of background pictures,
representing the significance of the left position of the kth significance map,
representing the significance of the left position of the kth significance map,
showing the significance of the upper edge position of the kth significance map,
the saliency at the bottom position of the kth saliency map is shown.
The blank features of the poster are evaluated as the size of the poster area occupied by the text box and the picture saliency block, and the blank features of the poster are evaluated as follows:
calculating the blank proportion P of the blank of the poster contentwhite：
Area(T)kArea of the K-th character frame, area (P)kArea of the K background picture, area (total) of the design finished product;
② normalizing the proportion of the remaining white, classifyingThe normalized leave-in-white feature evaluation score SWhite space：
The overlap characteristics for the text box and the picture are evaluated as:
calculating a total graph of all background pictures in the poster after being superposed according to the layers, and calculating a saliency map of the background pictures:
Area(P)kthe area of the K background picture is shown, and m represents the total number of the background pictures;
calculating the shielding proportion:
wherein the content of the first and second substances,
the image area of the superposition position of the image area and the character area is represented;
thirdly, normalization processing is carried out on the shielding proportion, and after normalization processing, the characteristic score S is overlappedOverlap：
The optimization design module automatically carries out parameter change operation on each constituent parameter of the text box attribute and the background graph attribute respectively, and marks the planar design layout state obtained after the nth parameter change operation as an environmental state SnAmbient state SnObtained by superposing the characteristic evaluation scores obtained by the scoring module, namely Sn=SAlignment of+SNormalization+SBalancing+SWhite space+SOverlapComputing environment stateState SnThe environmental score function of (1), (Sn); meanwhile, the optimization design module calculates an action execution probability function P (an) of the nth parameter change operation according to the average distribution probability, wherein P (an) = 1/N, and N represents the total number of parameter change operations; the optimization design module obtains an action expected value E of the nth parameter change operation according to an environment score function R (Sn) and an action execution probability function P (an)n，En= p (an) x R (Sn); the optimization design module changes the action expectation value E corresponding to each parameternPerforming accumulation calculation to obtain the maximum expected action value EmaxAnd the action expectation value E is setmaxAnd (4) executing the corresponding parameter change operation on the design finished product to obtain the optimized design finished product.
In conclusion, the device for automatically evaluating the layout quality and optimization of the planar design can evaluate the quality of the designed finished product so as to adjust and optimize the designed finished product by self, thereby improving the quality of the designed finished product and having strong practicability.
The above description is only an embodiment utilizing the technical content of the present disclosure, and any modification and variation made by those skilled in the art can be covered by the claims of the present disclosure, and not limited to the embodiments disclosed.
Claims (6)
1. An automatic evaluate the planar design layout quality and optimization device, its characterized in that: the system comprises a design structure analysis module, a grading module and an optimization design module;
the design structure analysis module converts a picture format file of a designed finished product into a structured file, and can obtain a text frame attribute and a background picture attribute of the designed finished product according to the structured file, wherein the text frame attribute comprises the frame size of a text frame and the position of the text frame, and the background picture attribute comprises the size of the background picture and color elements of the background picture;
the scoring module obtains the character frame attribute and the background image attribute through the structured file output by the structure analysis module so as to perform design quality scoring, wherein the design quality scoring comprises alignment feature evaluation on the character frame, regularity feature evaluation on the character frame, balance feature evaluation on the character frame and the image, blank feature evaluation on the poster and overlapping feature evaluation on the character frame and the image;
the optimization design module automatically carries out parameter change operation on each constituent parameter of the text box attribute and the background graph attribute respectively, and marks the planar design layout state obtained after the nth parameter change operation as an environmental state SnAmbient state SnCalculating the environment state S by superposing all the characteristic evaluation scores obtained by the scoring modulenThe environmental score function of (1), (Sn); meanwhile, the optimization design module calculates an action execution probability function P (an) of the nth parameter changing operation according to the average distribution probability, wherein P (an) is 1/N, and N represents the total number of parameter changing operations; the optimization design module obtains an action expected value E of the nth parameter change operation according to an environment score function R (Sn) and an action execution probability function P (an)n，EnP (an) × r (sn); the optimization design module changes the action expectation value E corresponding to each parameternPerforming accumulation calculation to obtain the maximum expected action value EmaxAnd the action expectation value E is setmaxAnd (4) executing the corresponding parameter change operation on the design finished product to obtain the optimized design finished product.
2. The apparatus for automatically evaluating the quality and optimization of a floor plan layout of claim 1 wherein the alignment characteristics of the text boxes are evaluated to calculate the alignment of all text boxes; the alignment characteristics for the text box were evaluated as:
calculating 6 dimensional coordinate positions of upper, lower, left, right, horizontal middle points and vertical middle points of each text frame, and marking each text frame as T1，T2，T3…Tn，TnThe data structure representing the dimension coordinate position of the nth text box and the text box frame is represented as Tn{Tn(up),Tn(down),Tn(left),Tn(right),Tn(horizion),Tn(veritical)}；
Respectively calculating histograms of 6 dimensional coordinate positions, and calculating an average value M of the 6 dimensional coordinate positions:
Mup＝(T1(up)+T2(up)+…+Tn(up))/2；
Mdown＝(T1(down)+T2(down)+…+Tn(down))/2；
Mleft＝(T1(left)+T2(left)+…+Tn(left))/2；
Mright＝(T1(lright)+T2(lright)+…+Tn(lright))/2；
Mhorizion＝(T1(horizion)+T2(horizion)+…+Tn(horizion))/2；
Mveritical＝(T1(veritical)+T2(veritical)+…+Tn(veritical))/2；
calculating the dispersion degree D of the 6 dimensional coordinate positions according to the histograms of the 6 dimensional coordinate positions, wherein the dispersion degree is an alignment score;
selecting one dimension with the lowest discrete degree in the 6 dimensional coordinate positions as one alignment mode, and selecting the discrete degree fraction of the alignment mode as the final alignment fraction SAlignment ofI.e. by
SAlignment of＝min(Dup,Ddown,Dleft,Dright,Dhorizion,Dvertical)。
3. The apparatus for automatically evaluating layout quality and optimization of a floor plan as claimed in claim 1, wherein the regularity characteristic of the text box is evaluated to calculate the consistency of the width or height of each text box frame; the regularity characteristics for the text box were evaluated as:
firstly, obtaining the width and height data of each text frame, marking each text frame as T1，T2，T3…Tn，TnRepresenting the nth text box, the dimensional coordinate position data structure of the text box frame being represented as Tn{T n(width),Tn(hight)}；
Calculating the average value M of the width and height data of each text frame:
Mwidth＝(T1(width)+T2(width)+…+Tn(width))/3；
Mhight＝(T1(hight)+T2(hight)+…+Tn(hight)/3；
calculating the variance of the width and height data of each text frame:
selecting the minimum variance D of the two variancesmin＝min(Dwidth，Dhight)；
Fifthly, carrying out normalization calculation on the minimum variance to obtain a regularity score SNormalization＝1/(1+Dmin)。
4. The apparatus for automatically evaluating the quality and optimization of a floor plan layout according to claim 1, wherein the balance features of the text box and the picture are evaluated to calculate the upper and lower and left and right symmetries of the visual saliency map; the balance characteristics for the text box and the picture are evaluated as:
setting the importance of the text frame as 1, setting the importance of the background picture as an interval of 0-1, calculating a total graph after all the picture layers are superposed, and calculating a significance graph of the total graph:
marking n character frames as T1，T2，T3…Tn，T1＝1,T2＝1,…Tn1 is ═ 1; marking m background pictures as P respectively1，P2，P3…Pm，P1＝random(0,1)＝P2＝P3＝…＝Pm；
② calculating the significance T of the text boxsalAnd background Picture saliency Psal：
thirdly, the significance P of the background picture obtained by calculationsalSignificance with text box TsalOverlapping to obtain a final significance map PfianlI.e. Pfianl＝Psal+Tsal；
Fourthly, calculating a final significance map PfianlTo obtain a balance score SBalancing：
Where m is the total number of background pictures,
representing the significance of the left position of the kth significance map,
representing the significance of the left position of the kth significance map,
showing the significance of the upper edge position of the kth significance map,
the saliency at the bottom position of the kth saliency map is shown.
5. The apparatus for automatically evaluating the quality and optimization of a floor plan layout of claim 1 wherein the whiteout characteristics of the poster are evaluated as occupying the size of the poster area for the text box and the graphic saliency blocks, the whiteout characteristics of the poster are evaluated as:
calculating the blank proportion P of the blank of the poster contentwhite：
Area(T)kArea of the K-th character frame, area (P)kArea of the K background picture, area (total) of the design finished product;
normalizing the blank ratio to obtain a blank characteristic evaluation score SWhite space：
SWhite space＝(1-Pwhite)*100。
6. The apparatus for automatically evaluating the quality and optimization of a floor plan layout as claimed in claim 1, wherein the overlap characteristics of the text box and the picture are evaluated as:
calculating a total graph of all background pictures in the poster after being superposed according to the layers, and calculating a saliency map of the background pictures:
Area(P)kthe area of the K background picture is shown, and m represents the total number of the background pictures;
calculating the shielding proportion:
wherein, Psal-textcorsswithpicturesThe image area of the superposition position of the image area and the character area is represented;
thirdly, normalization processing is carried out on the shielding proportion, and after normalization processing, the characteristic score S is overlappedOverlap：
SOverlap＝(1-Pblocked)*100。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810124753.1A CN108427828B (en) | 2018-02-07 | 2018-02-07 | Device for automatically evaluating layout quality and optimizing planar design |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810124753.1A CN108427828B (en) | 2018-02-07 | 2018-02-07 | Device for automatically evaluating layout quality and optimizing planar design |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108427828A CN108427828A (en) | 2018-08-21 |
| CN108427828B true CN108427828B (en) | 2022-04-26 |
Family
ID=63156504
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810124753.1A Active CN108427828B (en) | 2018-02-07 | 2018-02-07 | Device for automatically evaluating layout quality and optimizing planar design |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108427828B (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102611938B1 (en) * | 2018-12-04 | 2023-12-08 | 구글 엘엘씨 | Generate integrated circuit floorplans using neural networks |
| CN109670262B (en) * | 2018-12-28 | 2021-04-27 | 江苏艾佳家居用品有限公司 | Computer-aided home layout optimization method and system |
| CN112347600A (en) * | 2019-08-07 | 2021-02-09 | 广东博智林机器人有限公司 | Optimization method and device of planar design, electronic equipment and storage medium |
| CN112446561A (en) * | 2019-08-13 | 2021-03-05 | 广东博智林机器人有限公司 | Advertisement design drawing quality detection method and device |
| CN112580249A (en) * | 2019-09-11 | 2021-03-30 | 广东博智林机器人有限公司 | Optimization method and device of planar design, electronic equipment and storage medium |
| CN110489933B (en) * | 2019-09-19 | 2022-12-20 | 广东博智林机器人有限公司 | Method and system for generating planar design framework |
| CN110569493B (en) * | 2019-11-05 | 2020-11-06 | 广东博智林机器人有限公司 | Method and system for adjusting planar design framework |
| CN112184660A (en) * | 2020-09-25 | 2021-01-05 | 大方众智创意广告(珠海)有限公司 | Design image evaluation method and device and electronic equipment |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6748283B2 (en) * | 2000-09-29 | 2004-06-08 | Ford Motor Company | Method of using neutral event specification file for manufacturing line analysis |
| CN1648892A (en) * | 2004-01-19 | 2005-08-03 | 深圳市国际企业服务有限公司 | Uniform picture composing design method for modern city |
| CN101216710A (en) * | 2007-12-28 | 2008-07-09 | 东南大学 | Self-adapting selection dynamic production scheduling control system accomplished through computer |
| US7725857B2 (en) * | 2007-04-19 | 2010-05-25 | International Business Machines Corporation | Method for optimizing organizational floor layout and operations |
| CN101887467A (en) * | 2009-05-11 | 2010-11-17 | 复旦大学 | Method for establishing copper interconnection chemical mechanically mechanical polishing process model |
| CN102023570A (en) * | 2009-09-09 | 2011-04-20 | 西门子公司 | Method for computer-supported learning of a control and/or regulation of a technical system |
| CN104807468A (en) * | 2014-11-13 | 2015-07-29 | 厦门大学 | Automatic reduction and layout optimization method of multi-destination map and system thereof |
| CN104884862A (en) * | 2012-10-24 | 2015-09-02 | 视瑞尔技术公司 | Illumination device |
| CN105335812A (en) * | 2015-09-23 | 2016-02-17 | 程艳 | Picture optimization processing system and picture optimization processing method |
| CN105867427A (en) * | 2016-04-18 | 2016-08-17 | 苏州大学 | Robot routing on-line control method oriented to dynamic environments |
| WO2016192964A1 (en) * | 2015-05-29 | 2016-12-08 | Asml Netherlands B.V. | Simulation of lithography using multiple-sampling of angular distribution of source radiation |
| CN106445888A (en) * | 2016-09-30 | 2017-02-22 | 广州视睿电子科技有限公司 | Wordart manufacturing method and device |
| WO2017120895A1 (en) * | 2016-01-15 | 2017-07-20 | City University Of Hong Kong | System and method for optimizing user interface and system and method for manipulating user's interaction with interface |
| CN106997223A (en) * | 2016-01-25 | 2017-08-01 | 姜洪军 | Mobile visual field |
| CN107528712A (en) * | 2016-06-22 | 2017-12-29 | 中兴通讯股份有限公司 | The determination of access rights, the access method of the page and device |
| CN107609613A (en) * | 2017-09-18 | 2018-01-19 | 哈尔滨成长科技有限公司 | Go over examination papers information processing method, device, readable storage medium storing program for executing and electronic equipment |
| CN107633741A (en) * | 2017-10-31 | 2018-01-26 | 南京工业职业技术学院 | Space curve and stochastic variable numerical characteristic geometry demonstrator |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020019837A1 (en) * | 2000-08-11 | 2002-02-14 | Balnaves James A. | Method for annotating statistics onto hypertext documents |
-
2018
- 2018-02-07 CN CN201810124753.1A patent/CN108427828B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6748283B2 (en) * | 2000-09-29 | 2004-06-08 | Ford Motor Company | Method of using neutral event specification file for manufacturing line analysis |
| CN1648892A (en) * | 2004-01-19 | 2005-08-03 | 深圳市国际企业服务有限公司 | Uniform picture composing design method for modern city |
| US7725857B2 (en) * | 2007-04-19 | 2010-05-25 | International Business Machines Corporation | Method for optimizing organizational floor layout and operations |
| CN101216710A (en) * | 2007-12-28 | 2008-07-09 | 东南大学 | Self-adapting selection dynamic production scheduling control system accomplished through computer |
| CN101887467A (en) * | 2009-05-11 | 2010-11-17 | 复旦大学 | Method for establishing copper interconnection chemical mechanically mechanical polishing process model |
| CN102023570A (en) * | 2009-09-09 | 2011-04-20 | 西门子公司 | Method for computer-supported learning of a control and/or regulation of a technical system |
| CN104884862A (en) * | 2012-10-24 | 2015-09-02 | 视瑞尔技术公司 | Illumination device |
| CN104807468A (en) * | 2014-11-13 | 2015-07-29 | 厦门大学 | Automatic reduction and layout optimization method of multi-destination map and system thereof |
| WO2016192964A1 (en) * | 2015-05-29 | 2016-12-08 | Asml Netherlands B.V. | Simulation of lithography using multiple-sampling of angular distribution of source radiation |
| CN105335812A (en) * | 2015-09-23 | 2016-02-17 | 程艳 | Picture optimization processing system and picture optimization processing method |
| WO2017120895A1 (en) * | 2016-01-15 | 2017-07-20 | City University Of Hong Kong | System and method for optimizing user interface and system and method for manipulating user's interaction with interface |
| CN106997223A (en) * | 2016-01-25 | 2017-08-01 | 姜洪军 | Mobile visual field |
| CN105867427A (en) * | 2016-04-18 | 2016-08-17 | 苏州大学 | Robot routing on-line control method oriented to dynamic environments |
| CN107528712A (en) * | 2016-06-22 | 2017-12-29 | 中兴通讯股份有限公司 | The determination of access rights, the access method of the page and device |
| CN106445888A (en) * | 2016-09-30 | 2017-02-22 | 广州视睿电子科技有限公司 | Wordart manufacturing method and device |
| CN107609613A (en) * | 2017-09-18 | 2018-01-19 | 哈尔滨成长科技有限公司 | Go over examination papers information processing method, device, readable storage medium storing program for executing and electronic equipment |
| CN107633741A (en) * | 2017-10-31 | 2018-01-26 | 南京工业职业技术学院 | Space curve and stochastic variable numerical characteristic geometry demonstrator |
Non-Patent Citations (2)
| Title |
|---|
| Integrating systematic layout planning with fuzzy constraint theory to design and optimize the facility layout for operating theatre in hospitals;Qing-Lian Lin 等;《J Intell Manuf》;20151231;第87-89页 * |
| 基于OPENGL的计算机人物平面设计优化;袁霞 等;《电脑知识与技术》;20180131;第203-205页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108427828A (en) | 2018-08-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108427828B (en) | Device for automatically evaluating layout quality and optimizing planar design | |
| JP3063073B2 (en) | Image analysis expression adding device | |
| CN102005059B (en) | Image processing apparatus and image processing method | |
| CN103984953B (en) | Semantic segmentation method based on multiple features fusion Yu the street view image of Boosting decision forests | |
| US8132096B1 (en) | Image composition evaluation | |
| CN110377285B (en) | Method and device for generating page skeleton screen and computer equipment | |
| CN107833276A (en) | Two-dimensional map changes the method, apparatus and computer-readable storage medium of three-dimensional map | |
| US20050223319A1 (en) | Layout-rule generation system, layout system, layout-rule generation program, layout program, storage medium, method of generating layout rule, and method of layout | |
| CN101553845B (en) | Image dominant line determination and use | |
| US20190056854A1 (en) | Developing a non-rectangular user interface | |
| CN104134234A (en) | Full-automatic three-dimensional scene construction method based on single image | |
| US10210636B2 (en) | Automatic snap for digital sketch inking | |
| DE102018008275A1 (en) | Refine local parameterizations for the transmission of two-dimensional images to three-dimensional models | |
| CN102156688B (en) | Character transforming effect processing method and device | |
| WO2023097990A1 (en) | Element layout method and related device | |
| CN110659371B (en) | Automatic batch generation method and device for banner images of target objects | |
| CN103136781A (en) | Method and system of generating three-dimensional virtual scene | |
| US11144717B2 (en) | Automatic generation of document layouts | |
| CN110008450A (en) | Generation method, device, equipment and the medium of picture | |
| CN105809716A (en) | Superpixel and three-dimensional self-organizing background subtraction algorithm-combined foreground extraction method | |
| CN115063785B (en) | Method and device for positioning license plate in expressway scene by using target recognition model | |
| CN108596992B (en) | Rapid real-time lip gloss makeup method | |
| DE102013215301A1 (en) | System, method and computer program product for extruding a model through a two-dimensional scene | |
| CN104321811B (en) | Method and apparatus for dimensional printing | |
| CN108399288B (en) | Device for automatically adding decorative elements in planar design |
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 |