• Korean Journal of Cognitive Science
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• v.7 no.1
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• pp.57-74
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• 1996

This paper presents a comparison of recognition performance of the features used inthe recent handwritten korean character recognition.This research aims at providing the basis for feature selecion in order to improve not only the recognition rate but also the efficiency of recognition system.For the comparison of feature performace,we analyzed the characteristics of theose features and then,classified them into three rypes:global feature(image transformation)type,statistical feature type,and local/ topological feature type.For each type,we selected four or five features which seem more suitable to represent the characteristics of korean alphabet,and performed recongition experiments for the first consonant,horizontal vowel,and vertical vowel of a korean character, respectively.The classifier used in our experiments is a multi-layered perceptron with one hidden layer which is trained with backpropagation algorithm.The training and test data in the experiment are taken from 30sets of PE92. Experimental results show that 1)local/topological features outperform the other two type features in terms of recognition rates 2)mesh and projection features in statical feature type,walsh and DCT features in global feature type,and gradient and concavity features in local/topological feature type outperform the others in each type, respectively.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.97-107
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• 2024

Despite the rapid advancement in image recognition technology, achieving perfect digitization of tabular documents and handwritten documents still challenges. The purpose of this study is to improve the accuracy of digitizing the logbook by correcting errors by utilizing associated rules considered during logbook entries. Through this, it is expected to enhance the accuracy and reliability of data extracted from logbook through OCR programs. This model is to improve the accuracy of digitizing the logbook of the training ship "Saenuri" at the Mokpo Maritime University by correcting errors identified after Optical Character Recognition (OCR) program recognition. The model identified and corrected errors by utilizing associated rules considered during logbook entries. To evaluate the effect of model, the data before and after correction were divided by features, and comparisons were made between the same sailing number and the same feature. Using this model, approximately 10.6% of errors out of the total estimated error rate of about 11.8% were identified, and 56 out of 123 errors were corrected. A limitation of this study is that it only focuses on information from Dist.Run to Stand Course sections of the logbook, which contain navigational information. Future research will aim to correct more information from the logbook, including weather information, to overcome this limitation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.11
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• pp.140-149
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• 1996

Cursive characters are written on an economical principle to reduce the motion of a pen in the limit of distinction between characters. That is, the pen is not lifted up to move for writing a next stroke, the pen is not moved at all, or connected two strokes chance their shapes to a similar and simple shape which is easy to be written. For these reasons, strokes and korean alphabets are not only easy to be changed, but also difficult to be splitted. In this paper, we propose a curvature stroke modeling method for splitting and matching by using a structural primitive. A curvature stroke is defined as a substroke which does not change its curvanture. Input strokes handwritten in a cursive style are splitted into a sequence of curvature strokes by segmenting the points which change the direction of rotation, which occur a sudden change of direction, and which occur an excessive rotation Each reference of korean alphabets is handwritten in a printed style and is saved as a sequence of curvature strikes which is generated by splitting process. And merging process is used to generate various sequences of curvature strikes for matching. Here, it is also considered that imaginary strokes can be written or omitted. By using a curvature stroke as a unit of recognition, redundant splitting points in input characters are effectively reduced and exact matching is possible by generating a reference curvature stroke, which consists of the parts of adjacent two korean alphasbets, even when the connecting points between korean alphabets are not splitted. The results showed 83.6% as recognition rate of the first candidate and 0.99sec./character (CPU clock:66MHz) as processing time.