Title :
Meaningful Segmentation of Offline Individual Handwritten Numeric Characters
Author :
Batuwita, K.B.M.R. ; Bandara, G.E.M.D.C.
Abstract :
Fuzzy logic plays a vital role in handwriting recognition, since a fuzzy character recognition system with an automatically generated rule base possesses the features of flexibility, efficiency and online adaptability. One of the major requirements of such a fuzzy system is the segmentation of individual characters into meaningful segments. Then these segments can be used for the extraction of fuzzy features of the handwritten characters. This paper describes two algorithms for the meaningful segmentation of individual offline handwritten numeric skeletons.
Keywords :
fuzzy logic; fuzzy systems; handwriting recognition; handwritten character recognition; image recognition; image segmentation; knowledge based systems; fuzzy character recognition system; fuzzy logic; handwriting recognition; meaningful segmentation; offline individual handwritten numeric character; rule base system; Character generation; Character recognition; Computer vision; Feature extraction; Fuzzy logic; Fuzzy systems; Handwriting recognition; Hidden Markov models; Object recognition; Skeleton;
Conference_Titel :
Fuzzy Systems, 2006 IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9488-7
DOI :
10.1109/FUZZY.2006.1681907