Developing a Fuzzy Feature-Based Online Bengali Handwritten Word Recognition System

2020 ◽  
pp. 577-590
Author(s):  
Nur-A-Alam Shiddiki ◽  
Mohammed Moshiul Hoque
Keyword(s):  
Word Recognition ◽  
Recognition System ◽  
Feature Based ◽  
Handwritten Word Recognition

Online Handwritten Gujarati Word Recognition

2019 ◽  
Vol 9 (1) ◽  
pp. 35-50 ◽  
Author(s):  
Vishal A. Naik ◽  
Apurva A. Desai
Keyword(s):  
Word Recognition ◽  
Recognition System ◽  
Support Vector ◽  
Post Processing ◽  
Mapping Rule ◽  
Hybrid Features ◽  
Rule Based ◽  
Chain Code ◽  
Handwritten Word Recognition ◽  
Gujarati Language

In this article, an online handwritten word recognition system for the Gujarati language is presented by combining strokes, characters, punctuation marks, and diacritics. The authors have used a support vector machine classification algorithm with a radial basis function kernel. The authors used a hybrid features set. The hybrid feature set consists of directional features with curvature data. The authors have used a normalized chain code and zoning-based chain code features. Words are a combination of characters and diacritics. Recognized strokes require post-processing to form a word. The authors have used location-based and mapping rule-based post-processing methods. The authors have achieved an accuracy of 95.3% for individual characters, 91.5% for individual words, and 83.3% for sentences. The average processing time for individual characters is 0.071 seconds.

An Off-Line Cursive Handwritten Word Recognition System and Its Application to Legal Amount Interpretation

1997 ◽  
Vol 11 (05) ◽  
pp. 757-770 ◽  
Author(s):  
Ke Han ◽  
Ishwar K. Sethi
Keyword(s):  
Word Recognition ◽  
Recognition System ◽  
Great Accuracy ◽  
Input Word ◽  
Postal Service ◽  
Indexing Scheme ◽  
Cursive Script ◽  
System Maps ◽  
Handwritten Word Recognition ◽  
Verification Process

Off-line cursive script recognition has got increasing attention during the last three decades since it is of interest in several areas such as banking and postal service. An off-line cursive handwritten word recognition system is described in this paper and is used for legal amount interpretation in personal checks. The proposed recognition system uses a set of geometric and topologic features to characterize each word. By considering the spatial distribution of these features in a word image, the proposed system maps each word into two strings of finite symbols. A local associative indexing scheme is then used on these strings to organize a vocabulary. When presented with an unknown word, the system uses the same indexing scheme to retrieve a set of candidate words likely to match the input word. A verification process is then carried out to find the best match among the candidate set. The performance of the proposed system has been tested with a legal amount image database from real bankchecks. The results obtained indicate that the proposed system is able to recognize legal amounts with great accuracy.

Ensemble classifier-based off-line handwritten word recognition system in holistic approach

2018 ◽  
Vol 12 (8) ◽  
pp. 1467-1474 ◽  
Author(s):  
Jija Das Gupta ◽  
Soumitra Samanta ◽  
Bhabatosh Chanda
Keyword(s):  
Word Recognition ◽  
Holistic Approach ◽  
Recognition System ◽  
Ensemble Classifier ◽  
Handwritten Word Recognition
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