HMM Based Approach for Handwritten Arabic Word Recognition Using the IFN/ENIT- Database

  title={HMM Based Approach for Handwritten Arabic Word Recognition Using the IFN/ENIT- Database},
  author={Mario Pechwitz and Volker M{\"a}rgner},
An offline recognition system for Arabic handwritten words is presented. The recognition system is based on a semi-continuous 1-dimensional HMM. From each binary word image normalization parameters were estimated. First height, length, and baseline skew are normalized, then features are collected using a sliding window approach. This paper presents these methods in more detail. Some parameters were modified and the consequent effect on the recognition results are discussed. Significant tests… CONTINUE READING
Highly Influential
This paper has highly influenced 17 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 136 citations. REVIEW CITATIONS
89 Citations
11 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 89 extracted citations

137 Citations

Citations per Year
Semantic Scholar estimates that this publication has 137 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 11 references

Cursive script recognition using Semi Continuous Hidden Markov Models in combination with simple features

  • R.-D. Bippus, M. Lehning
  • In European workshop on handwriting analysis and…
  • 1994
1 Excerpt

Ultra fast parallel countor tracking with application to thinning

  • U.S.A. Ferreira
  • Pattern Recognition,
  • 1994
1 Excerpt

Similar Papers

Loading similar papers…