Graphical drop caps indexing

Authors:
Hassan Chouaib;Florence Cloppet;Nicole Vincent
Affiliations:
Laboratoire CRIP5, Paris Descartes University-Paris 5, Paris, France;Laboratoire CRIP5, Paris Descartes University-Paris 5, Paris, France;Laboratoire CRIP5, Paris Descartes University-Paris 5, Paris, France
Venue:
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
Year:
2009

Citing 6
Cited 0

A vector space model for automatic indexing

Communications of the ACM
Ancient Initial Letters Indexing

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Use of power law models in detecting region of interest

Pattern Recognition
A Stochastic Algorithm for Feature Selection in Pattern Recognition

The Journal of Machine Learning Research
Towards optimal bag-of-features for object categorization and semantic video retrieval

Proceedings of the 6th ACM international conference on Image and video retrieval
Drop Caps Decomposition for Indexing a New Letter Extraction Method

ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a method for graphical drop caps indexing. Drop caps are extracted from old books. Finding a method classifying them according to styles defined by the historian is of considerable interest. The developed method is a statistical approach, where all possible patterns included in a pixel mask are processed in order to extract indexes that characterize the image. Then these indexes are used to classify a query drop cap by searching its most similar drop caps in the indexed base.