Title :
Offline Cursive Character Challenge: a New Benchmark for Machine Learning and Pattern Recognition Algorithms.
Author :
Camastra, Francesco ; Spinetti, Marco ; Vinciarelli, Alessandro
Author_Institution :
Naples Parthenope Univ., Napoli
Abstract :
Cursive character recognition is a challenging task due to high variability and intrinsic ambiguity of cursive letters. This paper presents C-Cube (Cursive Character Challenge), a new public-domain cursive character database. C-Cube contains 57293 cursive characters manually extracted from cursive handwritten words, including both upper and lower case versions of each letter. The database can be downoloaded from the Web and it provides predefined experimental protocols in order to compare rigorously the results obtained by different researchers
Keywords :
character recognition; image recognition; learning (artificial intelligence); visual databases; Cursive Character Challenge; cursive character recognition; cursive handwritten words; machine learning; pattern recognition; public-domain cursive character database; Character recognition; Classification algorithms; Databases; Feature extraction; Handwriting recognition; Machine learning; Machine learning algorithms; Pattern recognition; Protocols; Testing;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.895
