IDENTIFYING HANDS ON ANCIENT ATHENIAN INSCRIPTIONS: FIRST STEPS TOWARDS A DIGITAL APPROACH*

In this paper, a novel methodology is introduced for the identification of the workmen (hands) that carved ancient inscriptions. This methodology employs specific geometric characteristics of each letter and computes the mean value and variance of these characteristics for each one of the available inscriptions separately. Subsequently, we define original decision thresholds that make use of the statistical distribution of the difference of these values in order to attribute an inscription to a given hand. The inscriptions of the hands under consideration have been properly processed and all information extracted, both visual and statistical, is stored in a suitable database. Application of this methodology to nine Athenian inscriptions, some of which contain very similar letters, offered correct, clear-cut hand identification.

[1]  Eric Lecolinet,et al.  A Survey of Methods and Strategies in Character Segmentation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  S. Tracy.  Attic letter-cutters of 229 to 86 B.C , 1990 .

[3]  Horst Bunke,et al.  Writer identification using text line based features , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[4]  Sargur N. Srihari,et al.  On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Stephen V. Tracy,et al.  Athens and Macedon: Attic Letter-Cutters of 300 to 229 B.C. , 2003 .

[6]  Xiaoqing Ding,et al.  An effective writer verification algorithm using negative samples , 2004, Ninth International Workshop on Frontiers in Handwriting Recognition.

[7]  Tieniu Tan,et al.  Personal identification based on handwriting , 2000, Pattern Recognit..

[8]  George E. Kokolakis.  Bayesian classification and classification performance for independent distributions , 1981, IEEE Trans. Inf. Theory.

[9]  José Martínez-Aroza,et al.  A measure of quality for evaluating methods of segmentation and edge detection , 2001, Pattern Recognit..

[10]  Mario Köppen,et al.  A computer-based system to support forensic studies on handwritten documents , 2001, International Journal on Document Analysis and Recognition.

[11]  S. Tracy.  Athenian Democracy in Transition: Attic Letter-Cutters of 340 to 290 B.C. , 1996 .

[12]  Nafiz Arica,et al.  An overview of character recognition focused on off-line handwriting , 2001, IEEE Trans. Syst. Man Cybern. Syst..

[13]  Tieniu Tan,et al.  Writer identification based on handwriting , 1998 .

[14]  David S. Doermann,et al.  Machine printed text and handwriting identification in noisy document images , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Lambert Schomaker,et al.  Automatic writer identification using connected-component contours and edge-based features of uppercase Western script , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Gerhard Rigoll,et al.  Writer Adaptation for Online Handwriting Recognition , 2001, DAGM-Symposium.

[17]  King-Sun Fu,et al.  IEEE Transactions on Pattern Analysis and Machine Intelligence Publication Information , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.