• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.31-34
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• 2003

In this paper, we describe a method for separating text lines in handwritten Korean address images. The most remarkable feature of the proposed method is to use a modified projection technique. named a partial projection technique. A projection based text line separation method which projects the whole address image in horizontal direction to find split points for text line separation cannot avoid failing separation in case of images with a little skew or overlap between vertically neighboring text lines. To overcome this problem, we have introduced a partial projection technique which splits an address image into a few partial address images to be equal width and then project them each horizontally. The experiment done with 989 handwritten Korean address images extracted from live mails shows the superiority of the proposed method. The correct text-line separation rate fir the testing images was about 91.5％.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.904-911
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• 2003

In this paper, we propose an effective method for the distinction between machine-printed and handwritten Korean address images. It is important to know whether an input image is handwritten or machine-printed, because methods for handwritten image are quite different from those of machine-printed image in such applications as address reading, form processing, FAX routing, and so on. Our method consists of three blocks: valid connected components grouping, feature extraction, and classification. Features related to width and position of groups of valid connected components are used for the classification based on a neural network. The experiment done with live Korean address images has demonstrated the superiority of the proposed method. The correct classification rate for 3,147 testing images was about 98.85%.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.8-19
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• 2004

In this paper, we propose an efficient method for locating destination address block on both of machine-Printed and handwritten Korean mail piece images. The proposed method extracts connected components from the binary mail piece image, generates text lines by merging them, and then groups the text fines into nine clusters. The destination address block is determined by selecting some clusters. Considering the geometric characteristics of address information on Korean mail piece, we split a mail piece image into nine areas with an equal size. The nine clusters are initialized with the center coordinate of each area. A modified Manhattan distance function is used to compute the distance between text lines and clusters. We modified the distance function on which the aspect ratio of mail piece could be reflected. The experiment done with live Korean mail piece images has demonstrated the superiority of the Proposed method. The success rate for 1, 988 testing images was about 93.56%.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.39-42
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• 2017

Communication between human and machine is having been researched from last few decades and still it's a challenging task because human behavior is unpredictable. When it comes on handwritten digits almost each human has their own writing style. Handwritten digit recognition plays an important role, especially in the courtesy amounts on bank checks, postal code on mail address etc. In our study, we proposed an efficient feature extraction system for recognizing single digit number drawn by mouse or by a finger on a screen. Our proposed method combines basic image processing and reading the strokes of a line drawn. It is very simple and easy to implement in various platform as compare to the system which required high system configuration. This system has been designed, implemented, and tested successfully.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.642-649
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• 2011

Among the various aspects of offline handwritten character patterns, it is the great variety of writing styles and variations that renders the task of computer recognition very hard. The immense variety of character shape has been recognized but rarely studied during the past decades of numerous research efforts. This paper tries to address the problem of measuring image distortions and handwritten character patterns with respect to reference patterns. This work is based on mass-spring mesh model with the introduction of simulated electric charge as a source of the external force that can aid decoding the shape distortion. Given an input image and a reference image, the charge is defined, and then the relaxation procedure goes to find the optimum configuration of shape or patterns of least potential. The relaxation process is based on the fourth order Runge-Kutta algorithm, well-known for numerical integration. The proposed method of modeling is rigorous mathematically and leads to interesting results. Additional feature of the method is the global affine transformation that helps analyzing distortion and finding a good match by removing a large scale linear disparity between two images.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.192-195
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• 2002

About 90% of Thai-style addresses have similar features; e.g. the beginning of each address line is diagonal. In this paper, we propose a method for locating destination address block (DAB) on Thai envelopes based on features of Thai-style addresses. Firstly, we decompose image into smaller blocks and remove all blocks not meeting criteria. Secondly, we search for the DAB candidates. Lastly, heuristic rules and typical features are applied to identify the destination address block. Experimental results using 2,700 envelopes of handwritten and machine printed Thai envelopes show a successful address extraction rate of 91%.

• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.813-821
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• 2001

While recognition of isolated units of writing, such as a character or a word, has been extensively studied, emphasis on the segmentation itself has been lacking. In this paper we propose an active segmentation method for handwritten Hangul address strings based on the Run-length code. A slant correction algorithm, which is considered as an important preprocessing step for the segmentation, is presented. Three fundamental candidate estimation functions are introduced to detect the clues on touching points, and the classification of touching types is attempted depending on the structural peculiarity of Hangul. Our experiments show segmentation performance of 88.2% on touching characters with minimal over-segmentation.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.93-102
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• 2003

A slant correction method for handwritten Korean strings based on analysis of stroke distribution, which effectively reflects structural properties of Korean characters, is presented in this paper. The method aims to deal with typical problems which have been frequently observed in slant correction of handwritten Korean strings with conventional approaches developed for English/European languages. Extracted strokes from a line of text image are classified into two clusters by applying the K-means clustering. Gaussian modeling is applied to each of the clusters and the slant angle is estimated from the model which represents the vertical strokes. Experimental results support the effectiveness of the proposed method. For the performance comparison 1,300 handwritten address string images were used, and the results show that the proposed method has more superior performance than other conventional approaches.

• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.1
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• pp.25-30
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• 2000

Hangul is regarded as one of the difficult character set due to the large number of classes and the shape similarity among different characters. Most of the conventional researches attempted to recognize the 2,350 characters which are popularly used, but this approach has a problem or low recognition performance while it provides a generality. On the contrary, recognition of a small character set appearing in specific fields like postal address or bank checks is more practical approach. This paper describes a research for recognizing the handwritten Hangul characters appearing in monetary fields. The modular neural network is adopted for the classification and three kinds of feature are tested. The experiment performed using standard Hangul database PE92 showed the correct recognition rate 91.56%.