• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3530-3538
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• 1999

In this paper, we propose a novel method for feature extraction of off-line handwritten characters recognition based on human optical neural field model. The proposed feature extraction system divide into three parts ; 1) smoothing process, 2) removing boundaries(boundary lines), 3) extracting feature information. The proposed system first removes rough pixels which are easy to occur in handwritten characters. The system then extracts and removes the boundary information which have no influence on characters recognition. Finally, the feature information for off-line handwritten characters recognition is extracted. With PE2 Hangul database, we perform feature extraction experiments for off-line handwritten characters recognition. In the experiment results, the proposed system based on optical neural field shows that can extract the feature information of off-line handwritten characters including curve lines, circles, quadrangles and so on.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.3
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• pp.385-392
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• 2006

This paper proposes a new stroke extraction algorithm for phoneme segmentation, which is one of main techniques for off-line handwritten Hangul recognition. The proposed algorithm extracts vertical, slant, and horizontal strokes from phonemes using run-length. The run-length of vertical or slant strokes becomes the width, and also the number of horizontal run-lengths the width. After extracting horizontal strokes from phonemes, the algorithm links two continuous vertical or slant stokes with run-lengths of the strokes' width to represent the features of a character. The extracted strokes can be utilized to recognize a character, using template matching of strokes, which is being adopted in on-line handwritten Hangul recognition.

• Korean Journal of Cognitive Science
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• v.6 no.4
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• pp.51-71
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• 1995

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.375-382
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• 2002

Handwritten character recognition is classified into on-line handwritten character recognition and off-line handwritten character recognition. On-line handwritten character recognition has made a remarkable outcome compared to off-line hacdwritten character recognition. This method can acquire the dynamic written information such as the writing order and the position of a stroke by means of pen-based electronic input device such as a tablet board. On the contrary, Any dynamic information can not be acquired in off-line handwritten character recognition since there are extreme overlapping between consonants and vowels, and heavily noisy images between strokes, which change the recognition performance with the result of the preprocessing. This paper proposes a method that effectively extracts the stroke including dynamic information of characters for off-line Korean handwritten character recognition. First of all, this method makes improvement and binarization of input handwritten character image as preprocessing procedure using watershed algorithm. The next procedure is extraction of skeleton by using the transformed Lu and Wang's thinning: algorithm, and segment pixel array is extracted by abstracting the feature point of the characters. Then, the vectorization is executed with a maximum permission error method. In the case that a few strokes are bound in a segment, a segment pixel array is divided with two or more segment vectors. In order to reconstruct the extracted segment vector with a complete stroke, the directional component of the vector is mortified by using right-hand writing coordinate system. With combination of segment vectors which are adjacent and can be combined, the reconstruction of complete stroke is made out which is suitable for character recognition. As experimentation, it is verified that the proposed method is suitable for handwritten Korean character recognition.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.1002-1013
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• 1996

The segmentation of characters is an important step in the automatic recognition of handwritten text. This paper proposes the segmenting method of off-line handwritten Hangul. The suggested approach is based on the structural characteristics of Hangul. The first step extracts the local features. connected component and strokes from the imput word. In the second step we identify the class of strokes. The third segmenting step specifies WRC(White Run Column) before consonant or horizontal vowel. If the segment is longer than threshold, the system estimates segmenting columns using the consonant-vowel information and column features, and then finds a cornered boundary along the strokes within the estimated segmenting columns.

• Korean Journal of Cognitive Science
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• v.7 no.4
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• pp.63-74
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• 1996

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.887-894
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• 2006

This paper proposes a new method that detects the intersection points of handwritten Hangul strokes using run-length. The method firstly finds the strokes' width of handwritten Hangul characters using both horizontal and vertical run-lengths, secondly extracts horizontal and vertical strokes of a character utilizing the strokes' width, and finally detects the intersection points of the strokes exploiting horizontal and vertical strokes. The analysis of both the horizontal and the vertical strokes doesn't use the strokes' angles but both the strokes' width and the changes of the run-lengths. The intersection points of the strokes become the candidated parts for phoneme segmentation, which is one of main techniques for off-line handwritten Hangul recognition. The segmented strokes represent the feature for handwritten Hangul recognition.

• Journal of the Korea Computer Industry Society
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• v.3 no.5
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• pp.575-584
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• 2002

On-line handwritten character recognition be achieved successful results since effectively neural networks divided the letter which is the time ordering of strokes and stroke position. But off-line handwritten character recognition is in difficulty of incomplete preprocessing because has not information of motion or time and has frequently overlap of the letter and many noise occurrence. consequently off-line handwritten character recognition needs study of various methods. This paper apply watershed algorithm to preprocessing for off-line handwritten hangul character recognition. This paper presents effective method in four steps in watershed algorithm as consider execution time of watershed algorithm and quality of result image. As apply watershed algorithm with effective structure to preprocessing, can get to the good result of image enhancement and binarization. In this experiment, this paper is estimate the previous method with this paper method for execution time and quality in image. Average execution time on the previous method is 2.16 second and Average execution time on this paper method is 1.72 second. While this paper method is remove noise effectively with overlap stroke, the previous method does not seem to be remove noise effectively with overlap stroke.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.819-822
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• 2000

The merit of the stroke extraction algorithm is the ease of the feature abstraction from the skeleton of a character, But, extracting strokes from Korean characters has two major problems that must be dealt with. One is extracting primitive strokes and the other is merging or splitting the strokes using dynamic information of the strokes. In this paper, a method is proposed to extract strokes from an off-line handwritten Korean character. We have developed some stroke segmentation rules based on splitting, merging and directional analysis. Using these techniques, we can extract and trace the strokes in an off-line handwritten Korean character accurately and efficiently.

• Korean Journal of Cognitive Science
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• v.4 no.1
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• pp.243-260
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• 1993

This paper presents an efficient method for estimationg and correcting the slant of off-line handwritten Hangul strings.In the proposed method,after extracting contours from input image.Hough tranform is applied to the contours to detect lines and estimate slants of the lines.When Hough trans form is applied to the contours,pixels which are not parts of the same stroke could be detected as a line.In order to exclude these lines from slant estimation process,detected lines which have the length less than threshold are eliminated.Experiments have been performed with address images which were extracted from live envelopes provided by Seoul Mail Center.Experimental results show that the proposed method is superior to the previous methods,which had been done with handwritten English strings.in estimation the slant of off-line handwritten Hangul strings.