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Automatic Color Matching with a Computer Kei Takahashi Dept. of Computer Science and Engineering Helsinki University of Technology.

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Presentation on theme: "Automatic Color Matching with a Computer Kei Takahashi Dept. of Computer Science and Engineering Helsinki University of Technology."— Presentation transcript:

1 Automatic Color Matching with a Computer Kei Takahashi Dept. of Computer Science and Engineering Helsinki University of Technology

2 How do you like these color pairs? Universally accepted pairs

3 How about these? Controversial pairs (Should be avoided)

4 Computerized Color Matching 1)Color matching: its importance 2)Our Approach: the judge machine 3)Application: automatic color adviser

5 1.1 Color matching: its importance Judge if two (or more) colors match or not Depend on persons and situations Still there are universally accepted pairs 1. Color matching: its importance

6 1.2 Commercial importance Coloring makes all the difference It changes customers impression Colorings improve/diminish the value Should avoid controversial pairs Needs to be unique and impressive Always new color designs are needed 1. Color matching: its importance

7 1.3 Growths of demands PC program offers infinite colors Everyone need to design PowerPoint, Word, websites… Always unique design is needed Color design is a tough work Cant afford to put out to professional designers 1. Color matching: its importance

8 2.1 The judge machine We designed a program which judges if a color pair is good or bad Good! Bad! 2. Our proposal : Judge machine

9 2.2 Machine Learning A computer can learn general knowledge from training data Not much number of training data are needed Bad examples Good examples Unknown data 2. Our proposal : Judge machine Good! Knowledge

10 2.2 Machine Learning (cont.) Prepare training data Evaluated by teacher Not so many data is needed (ex.100) Train a computer with the data The computer acquires general knowledge Now it can judge any color pairs Acts just as the teacher 2. Our proposal : Judge machine

11 2.3 Prototype experiment Prepared data : Classified good pairs and bad pairs by hand 200 examples Trained with the first 100 pairs Prepared Data Used for training Used for Evaluation Good Pairs Bad Pairs 2. Our proposal : Judge machine

12 2.3 Prototype experiment (cont.) Compared the judge of the computer and teacher (human) Accuracy was 80% >> Learning was successful! Computer Teacher Goo d BadGoo d 2. Our proposal : Judge machine

13 3. Automatic Color Adviser Generate infinite good color pairs Generate random color pairs Select pairs that passed the judgment Generate pairs randomly Good pairs are selected 3. Automatic Color Adviser Judge machine

14 3. Automatic Color Adviser (cont.) Practical applications : Website design PowerPoint presentations Word documents There are no similar function for now 3. Automatic Color Adviser

15 Conclusion Color matching is an important area Judge machine divides good/bad color pairs Infinite number of good color pairs are obtained in no time (Automatic Color Adviser)

16 Further Information Our website: SVM (machine learning)


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