LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Clarke, Eddie
Languages: English
Types: Unknown
Subjects:
A number of new techniques and approaches for off-line handwritten character recognition are presented which individually make significant advancements in the field. First. an outline-based vectorization algorithm is described which gives improved accuracy in producing vector representations of the pen strokes used to draw characters. Later. Vectorization and other types of preprocessing are criticized and an approach to recognition is suggested which avoids separate preprocessing stages by incorporating them into later stages. Apart from the increased speed of this approach. it allows more effective alteration of the character images since more is known about them at the later stages. It also allows the possibility of alterations being corrected if they are initially detrimental to recognition. A new feature measurement. the Radial Distance/Sector Area feature. is presented which is highly robust. tolerant to noise. distortion and style variation. and gives high accuracy results when used for training and testing in a statistical or neural classifier. A very powerful classifier is therefore obtained for recognizing correctly segmented characters. The segmentation task is explored in a simple system of integrated over-segmentation. Character classification and approximate dictionary checking. This can be extended to a full system for handprinted word recognition. In addition to the advancements made by these methods. a powerful new approach to handwritten character recognition is proposed as a direction for future research. This proposal combines the ideas and techniques developed in this thesis in a hierarchical network of classifier modules to achieve context-sensitive. off-line recognition of handwritten text. A new type of "intelligent" feedback is used to direct the search to contextually sensible classifications. A powerful adaptive segmentation system is proposed which. when used as the bottom layer in the hierarchical network. allows initially incorrect segmentations to be adjusted according to the hypotheses of the higher level context modules.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Hall, P.A.V. and Dowling, G.R. (1980), "Approximate String Matching," puting Surveys, vol. 12, no. 4, pp. 381-402.
    • Ho, S.-B. and Dyer, C.R. (1986), "Shape Smoothing Using Medial Axis Transform," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, pp. 512-520.
    • Hebb, D.O. (1949), "Chapter 4 - The First Stage of Perception: Growth of the Assembly," in The Organisation of Behaviour, John Wiley and Sons, New York, U.S.A.
    • Ho, Y.-C. and Kashyap, R.L. (1966), "A Class of Iterative Procedures for Linear Inequalities," SIAM Journal of Control, vol. 4, pp. 112-115.
    • Hu, C.-H., u, P., Ning, H.-Y. and Wu, F.-F. (1980), "A Handwritten Numeral Recognition Machine for Automatic Mail-Sorting,(rq in EUSIPCO-80 Signal Processing: Theories and Applications, ed. M. Kunt and F. de Coulon, NorthHolland, Amsterdam.
    • Hoare, C.A.R. (1962), "Quicksort," Computer Journal, vol. 5, pp. 10-15.
    • Hopfield, J.1. (1982), "Neural Networks and Physical Systems with Emergent Collective Computational Abilities," Proceedings of the National Academy of Sciences, vol. 79, pp. 2554-2558.
    • Hosking, K.H. (1972), "A Contour Method for the Recognition of Handprinted Characters," in Machine Perception of Patterns and Pictures, The Institute of Physics, London. England.
    • Hough, P.V.C (1962), "A Method and Means for Recognizing Complex Patterns," U.S. Patent 3069654.
    • Hanson, AR., Riseman, E.M. and Fisher, E. (1976), "Context in Word Recognition," Pattern Recognition, vol. 8, pp. 35-45.
    • Hunt, lE. and Szymanski, T.G. (1977), "Fast Algorithm for Computing Longest Common Subsequences," Communications of tilt!ACM, vol. 20, pp. 350-353.
    • HUll, J.1. and Srihari, S.N. (1982), "Experiments in Text Recognition with Binary N-Gram and Viterbi Algorithms," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 5, pp. 520-530.
    • Hull, J.1. and Srihari, S.N. (1986), "A Computational Approach to Word Shape Recognition: Hypothesis Generation and Testing," Proceedings of the IEEE-CS Conference on Computer Vision and Pattern Recognition, pp. 156-161.
    • Hertz, L. and Schafer, R.W. (1988), "Multilevel Thresholding Using Edge Matching," Computer Vision, Graphics and Image Processing, vol. 44, pp.
    • Hull, 11, Srihari, S.N. and Choudhari, R. (1983), "An Integrated Aigorithm for Text Recognition: Comparison with a Cascaded Algorithm." IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 5, no. 4, pp. 384-395.
    • Holt, C.M., Stewart, A, Clint, M. and Perrott. R.H. (1987), "An Improved Parallel Thinning Algorithm." Communications of tilt! ACM, vol. 30, no. 2, pp.
    • Hull, J.1., Srihari, S.N., Cohen, E., Kaan, L., Cullen. P. and Palumbo, P. (1988), "A Blackboard-Based Approach to Handwritten ZIP Code Recognition," Proceedings of the 9th International Conference on Pattern Recognition, vol. 1, pp. 111-113. IEEE, Rome, Italy.
    • Hopfield, J.1. and Tank. D.W. (1986). "Neural Computation of Decisions in Optimization Problems." Biological Cybernetics. vol. 52. pp. 141-152.
    • Hopfield, J.J. and Tank. D.W. (1986). "Computing with Neural Circuits: A Model." Science. vol. 233. pp. 625-633.
    • Hussain. AB.S .• Toussaint. G.T. and Donaldson. R.W. (1972), "Results Obtained Using a Simple Character Recognition Procedure on Munson's Kopec, G.E. and Chou, P.A. (1994), "Document Image Decoding Using Markov Source Models," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no. 6, pp. 602-617.
    • Kanal, L.N. and Dattatreya, G.R., "Pattern Recognition," pp. 720-729.
    • Kiryati, N., Eldar, Y. and Bruckstein, A.M. (1991), "A Probabilistic Hough Transform," Pattern Recognition, vol. 24, no. 4, pp. 303-316.
    • Kirkpatrick, S., Gelatt, C.D. and Vecchi, M.P. (1983), "Optimisation by Simulated Annealing," Science, vol. 220, pp. 671-680.
    • Kittler, J. and IlIingworth, J. (1985), "A Review of Relaxation Labelling Algorithms," Image and Vision Computing, vol. 3, no. 4. pp. 206-216.
    • Kashyap, R.L. and Oommen, B.J. (1984), "Spelling Correction Using Probabilistic Methods," Pattern Recognition Letters, vol. 2, no. 3, pp. 147-154.
    • Kohonen, T. (1982), "Self-Organized Formation of Topologically Correct Feature Maps." Biological Cybernetics, vol. 43. pp. 59-69.
    • Levenshtein, V.I. (1966), "Binary Codes Capable of Correcting Deletions, Insertions and Reversals," Soviet Physics-Doklady. vol. 10, no. 8, pp. 707-710, translated from Doklady Akademii Nauk SSSR, vol. 163, no. 4, pp. 845-848, 1965.
    • Levine, B. (1981), "Derivations of Tree Sets with Applications to Grammatical Inference," IEEE Transactions on Pattern Analysis and Machine Intelligence.
    • vol. 3, no. 3, pp. 285-293.
    • Leedham, C.G. and Friday, P.O., "Isolating Individual Handwritten Characters," pp.411-4n.
    • Lippman, R. and Gold, B. (1987), "Neural Net Classifiers Useful for Speech Recognition," Proceedings of the 1st IEEE International Conference on Neural Networks, vol. IV, pp. 417-426, IEEE, San Diego, U.S.A.
    • Liao, Y. -Z. (1981 ), "A Two-Stage Method of Fitting Conic Arcs and StraightLine Segments to Digitized Contours," Proceedings of the International Conference on Pattern Recognition and Image Processing. pp. 224-229, IEEE. Dallas.
    • Ln, H.E. and Wang, P.S.P. (1986), "A Comment on 'A Fast Parallel Thinning Algorithm for Digital Patterns,'" Communications of the ACM, vol. 29, no. 3, pp. 239-242.
    • Musavi, M.T., Ahmed, W., Chan, KH., Faris, K.B. and Hummels, n.M. (1992), "On the Training of Radial Basis Function Classifiers," Neural Networks, vol. 5, no. 4, pp. 595-603.
    • Maes, M. (1990), "On a Cyclic String-to-String Correction Problem," Information Processing Letters, vol. 35, pp. 73-78.
    • Maes, M. (1991), "Polygonal Shape Recognition Using String-Matching Techniques," Pattern Recognition, vol. 24, 00. 5, pp. 433-440.
    • Ni, G .• Ding. J .• Gao. Z. and Liu, J. (1980). "A Structural Method for Handprinted Alphanumeric and Other Symbols," Proceedings of tile 5tll International Conference on Pattern Recognition. pp. 726-728. IEEE.
    • Neuhoff. DL (1975), "The Viterbi Algorithm as an Aid in Text Recognition." IEEE Transactions on Information Theory, vol. 21, pp. 222-226.
    • Nevatia. R. (1986). "Chapter 9 - Image Segmentation." in Handbook of Pattern Recognition and Image Processing. ed. T.Y. Young and K.-S. Fu. pp.
    • 215-231. Academic Press.
    • Rosenfeld. A. (1973). "Array Grammar Normal Forms." Information and Control. vol. 23. no. 2. pp. 173-182.
    • Rosenfeld. A. and Pfaltz, J.L. (1968). "Distance Functions on Digital Pictures." Pattern Recognition. vol. 1. pp. 33-61.
    • Rutovitz, D. (1966). "Pattern Recognition." Journal of the Royal Statistics Society. vol. 129. Series A. pp. 504-530.
    • Rumelhart, D.E. and Zipser, D. (1985), "Feature DiSCOVery by Competetive Learning." Cognitive Science. vol. 9, pp. 75-112.
    • Suzuki, S. and Abe, K. (1987), "Binary Picture Thinning by an Iterative Parallel Two-Subcycle Operation," Pattern Recognition, vol. 10,110.3, pp. 297-307.
    • Sardana, H.K. (1993), Edge Moments in Pattern Recognition, University of Nottingham, Nottingham, England.
    • Suen, C.Y., Berthod, M. and Mori, S. (1980), "Automatic Recognition of Handprinted Characters - The State of the Art," Proceedings of the IEEE, vol. 68, 00. 4, pp. 469-487.
    • Sklansky, J., Chazin, R.L. and Hansen. BJ. (1972). "Minimum Perimeter Polygons of Digitized Silhouettes." IEEE Transactions on Computers. vol. 23.
    • pp. 445-448.
    • Schalkoff. R.J. (1989). Digital Image Processing and Computer Vision. John Wiley and Sons. New York. U.S.A.
    • Schalkoff, R.J. (1992). Pattern Recognition: Statistical, Structural and Neural Approaches, John Wiley and Sons. New York. U.S.A.
    • Szu, H. (1986), "Fast Simulated Annealing," in AlP Conference Proceedings 151: Neural Networks for Computing, ed. J. Denker, pp. 420-425, American Institute of Physics, New York, U.S.A.
    • Tsuji, Y. and Asai, K. (1984), "Character Image Segmentation," Proceedings of the Society of the Photo-Optical Institute of Engineers, vol. 504, Applications of Digital Image Processing VII, pp. 2-9.
    • Tsujimoto, S. and Asada, H. (1991), "Resolving Ambiguity in Resolving Touching Characters," Proceedings of the 1st International Conference on Document Analysis and Recognition, pp. 701-709, Saint-Malo, France.
    • Vossler, C.M. and Branston, N.M. (1964), "The Use of Context for Correcting Garbled English Text," Proceedings of the ACM 9th National Conference, pp.
    • D2 4-1-D2 4-13.
    • Viterbi, A.J. (1967), "Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm," IEEE Transactions on Information Theory. vol. 13. pp. 260-269.
    • Walsh. J.L. (1923). "A Closed Set of Normal Orthogonal Functions." American Journal of Mathematics. vol. 45. pp. 5-24.
    • Wang. P.S. (1980). "Some New Results on Isotonic Array Grammars." Informalion Processing utters. vol 10. no. 3. pp. 129-131.
    • Wasan, M.T. (1969). Stochastic Approximation. Cambridge University Press.
    • Yamada. H. and Mori, S. (1978), "Line-Wise Parallel Operations and Their Application to Handprint Recognition," Proceedings of the 4th International Joint Conference on Pattern Recognition, pp. 789-793, Kyoto, Japan.
    • Yamamoto, K. and Mori, S. (1980), "Recognition of Handprinted Characters by Outermost Point Method," Pattern Recognition, vol. 12, pp. 229-236.
    • Young, S.R. and Matessa, M. (1992), "MINDS-II Feedback Architecture: Detection and Correction of Speech Misrecognitions," Carnegie-Mellon University, Department of Computer Science, Technical Report CMU-CS-92-119.
    • Yokoi, S., Toriwaki, 1.-1. and Fukumura, T. (1973), "Topological Properties in Digitized Binary Pictures," Systems, Computers, Controls, vol. 4, DO. 6, pp. 32- 39.
    • Zadeh, L.A. (1965). "Fuzzy Sets," Information and Control, vol. 8, pp. 338-353.
    • Zahn, C.T. and Roskies, R.Z. (1972), "Fourier Descriptors for Plane Closed Curves," IEEE Transactions on Computers, vol. 21. no. 3, pp. 269-281.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article