Title :
Retrieval of Rashi Semi-cursive Handwriting via Fuzzy Logic
Author :
Gur, E. ; Zelavsky, Z.
Author_Institution :
Dept. of Electron. Eng., Jerusalem Coll. of Eng., Jerusalem, Israel
Abstract :
Text recognition and retrieval is a well known problem. Automated optical character recognition (OCR) tools do not supply a complete solution and in most cases human inspection is required. In this paper the authors suggest a novel text recognition algorithm based on usage of fuzzy logic rules relying on statistical data of the analyzed font. The new approach combines letter statistics and correlation coefficients in a set of fuzzy based rules, enabling the recognition of distorted letters that may not be retrieved otherwise. The authors focused on Rashi fonts associated with commentaries of the Bible that are actually handwritten calligraphy.
Keywords :
handwriting recognition; handwritten character recognition; optical character recognition; text detection; Bible; Rashi fonts; Rashi semicursive handwriting retrieval; analyzed font; automated optical character recognition tool; fuzzy based rules; fuzzy logic rules; handwritten calligraphy; human inspection; statistical data; text recognition algorithm; Character recognition; Correlation; Correlation coefficient; Engines; Fuzzy logic; Optical character recognition software; Text recognition; character recognition; document analysis systems; fuzzy logic;
Conference_Titel :
Frontiers in Handwriting Recognition (ICFHR), 2012 International Conference on
Conference_Location :
Bari
Print_ISBN :
978-1-4673-2262-1
DOI :
10.1109/ICFHR.2012.262