1 / 6

Painting Classification by Artist and Period Using Neural Network Pattern Classification Techniques

Painting Classification by Artist and Period Using Neural Network Pattern Classification Techniques Stuart Rowan 12/12/2008 Motivation Pattern classification techniques can be used to group paintings together It is desirable to group paintings by artist to detect forgeries

niveditha
Download Presentation

Painting Classification by Artist and Period Using Neural Network Pattern Classification Techniques

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Painting Classification by Artist and Period Using Neural Network Pattern Classification Techniques Stuart Rowan 12/12/2008

  2. Motivation • Pattern classification techniques can be used to group paintings together • It is desirable to group paintings by artist to detect forgeries • When art historians don’t have a clear historic record they group paintings by style to study an artist’s progression

  3. Goal • Discover features that can be used to classify paintings by artist and style • Apply these features and various pattern classifiers to problems surrounding van Gogh paintings such as forgery detection and period grouping.

  4. Van Gogh Features • Van Gogh has a distinctive brushstroke that creates texture in the painting • There are standard statistical measures of texture • Fourier Transforms can characterize the repetition of the brushstrokes

  5. Results

  6. Conclusion • Forgery detection has been accomplished • There is a trade off between feature extraction computation time and pattern classification computation time.

More Related