Document image compression and analysis
Document image compression and analysis
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lossless and lossy compression of text images by soft pattern matching
DCC '96 Proceedings of the Conference on Data Compression
Document Analysis in Gray Level and Typography Extraction Using Character Pattern Redundancies
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Document Images Analysis Solutions for Digital libraries
DIAL '04 Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL'04)
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
| Hi-index | 0.00 |
In this paper, we propose a new approach of similarity retrieval in ancient handwritten documents. Similarities are retrieved on shape fragments which can be analysed according to different granularities (from the grapheme to the character size) depending on the handwriting quality, regularity and sharpness. The approach is based on a “segmentation free” methodology which considers the image with all frequencies and Gray levels. The method has been applied for two purposes: to establish the basis of a new handwritings compression approach based on handwritten images specificities and to show that only shape fragments can efficiently be used for writer characterization. We present here the global methodology for the similarities characterization which lies on an oriented handwriting shapes decomposition. First results for data compression and writer characterization are very encouraging in a field where there is no anterior work.