Title :
An overview of segmentation techniques for handwritten connected digits
Author :
Kulkarni, R.V. ; Vasambekar, P.N.
Author_Institution :
Dept. of Comput. Sci. & Technol., Shivaji Univ., Vidyanagar, India
Abstract :
Machine recognition of handwritten numerals has practical significance. Segmentation of connected digits is being recognized as a critical task in the field of document image analysis and recognition. Higher recognition rates for isolated digits Vs those obtained for connected numeral strings exemplify the vital role of connected digits segmentation. The present overview describes various segmentation techniques for connected digits in general numeral strings and mathematical expressions, worked out in this decade.
Keywords :
handwritten character recognition; image recognition; image segmentation; connected numeral string; document image analysis; handwritten connected digits; handwritten numeral; machine recognition; segmentation technique; Algorithm design and analysis; Artificial neural networks; Feature extraction; Handwriting recognition; Image segmentation; Reservoirs; Skeleton; connected digits; handwritten numerals; number recognition; segmentation; touching numerals;
Conference_Titel :
Signal and Image Processing (ICSIP), 2010 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4244-8595-6
DOI :
10.1109/ICSIP.2010.5697522
