Abstract
A novel system for recognition of handprinted alphanumeric characters has been developed and tested. The system can be employed for recognition of either the alphabet or the numeral by contextually switching on to the corresponding branch of the recognition algorithm. The two major components of the system are the multistage feature extractor and the decision logic tree-type catagorizer. The importance of “good” features over sophistication in the classification procedures was recognized, and the feature extractor is designed to extract features based on a variety of topological, morphological and similar properties. An information feedback path is provided between the decision logic and the feature extractor units to facilitate an interleaved or recursive mode of operation. This ensures that only those features essential to the recognition of a particular sample are extracted each time. Test implementation has demonstrated the reliability of the system in recognizing a variety of handprinted alphanumeric characters with close to 100% accuracy.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
J. T. Tou and R. C. Gonzalez, “Recognition of handwritten characters by topological feature extraction and multi-level categorization,”IEEE Trans. Comput. C-21:776–785 (July 1972).
S. H. Unger, “Pattern recognition and detection,”Proc. IEE 47:1737–1752 (October 1959).
J. R. Parks, “A Multi-level System of Analysis for Mixed Font and Hand Block Printed Character Recognition,” inAutomatic Interpretation and Classification of Images, A. Grasselli, ed. (Academic Press, New York, 1969), pp. 295–322.
G. H. Granlund, “Fourier processing for handprint character recognition,”IEEE Trans. Comput. C-21:201–204 (February 1972).
D. Koxlay, “Feature Extraction in a Learning Optical Character Recognition Machine,” Symposium of Feature Extraction and Selection in Pattern Recognition at Argonne National Laboratory (October 1970).
G. Tauschek, “Reading Machine,” U. S. Pat. 2026329 (December 1935).
R. B. Hennis, “IBM 1975 optical page reader, part I-system design,”IBM J. Res. Dev. 12(5):346–353 (September 1968).
U. Niesser and P. Weene, “A note on human recognition of handprinted characters,”Inf. Control 3:191–196 (June 1960).
G. Nagy, “State of art in pattern recognition,”Proc. IEEE 56:836–862 (May 1968).
K. Fukunaga,Introduction to Statistical Pattern Recognition (Academic Press, New York, 1972).
J. S. Bomba, “Alphanumeric character recognition using local operations,”Proc. EJCC (1959).
F. C. Greanias et al., “The recognition of handwritten numerals by contour analysis,”IBM J. Res. Dev. 7:14–21 (January 1963).
I. H. Sublette and J. Tults, “Character recognition by digital feature extraction,”RCA Rev. 23:60–79 (March 1962).
H. Genchiet al., “Recognition of handprinted numerals for automatic mail sorting,”Proc. IEEE 56:1292–1301 (August 1968).
P. W. Weeks, “Rotating raster character recognition system,”AIEE Trans. SO, Pt. I, 353–359 (September 1961).
J. R. Singer, “A self organizing recognition system,”Proc. WJCC (1961).
A. B. S. Hussainet al., “Results on Munson's data,”IEEE Trans. Comput. C-21:201–204 (February 1972).
R. J. Spinrad, “Machine recognition of handprinting,”Inf. Control 8:124–142 (April 1965).
M. Beun, “A flexible method for automatic reading of handwritten numerals,” Phillips Technical Review, Vol.33, 1973, pp. 89–101.
R. Narasimhan, “Syntax directed interpretation of classes of pictures,”Commun. ACM 9:166–173 (March 1966).
M. Eden, “Handwriting and pattern recognition,”IRE Trans. Inf. Theory 8:160–172 (February 1962).
A. C. Shaw, “Parsing of graph representable pictures,”J. ACM 17:453–481 (July 1970).
R. Narasimhan, “A syntax-aided recognition scheme for handprinted English letters,”Pattern Recognition 3:345–361 (1971).
B. V. Dasarathy, “An integrated nonparametric sequential approach to multi-class pattern classification,”Int. J. Syst. Sci. 4:449–460 (1973).
K. P. Bharath Kumar, “An Innovative System for Recognition of Hand Printed Characters,” Master's thesis, Indian Institute of Science, School of Automation, Bangalore, India (1974).
Author information
Authors and Affiliations
Additional information
Most of this work was carried out at the School of Automation, Indian Institute of Science, Bangalore, India.
Rights and permissions
About this article
Cite this article
Dasarathy, B.V., Kumar, K.P.B. CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters. International Journal of Computer and Information Sciences 7, 253–282 (1978). https://doi.org/10.1007/BF00991633
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF00991633