• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.97-100
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• 2013

In this paper, we propose a detection method of the character rather than cursive, containing many components of the vertical and horizontal direction in complex background image. The characters have many dense corners but the background has few sparse corners. So we use harris corner detector and cluster the corners by using the position of the detected corners for detecting character regions. To merge or filter character regions, we analysis a histogram of gray image of character regions. In each improved region, we compare histograms of R, G, B channels to detect characters.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3086-3097
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• 2000

본 논문에서는 손으로 자유스럽게 그린 서식 문서에서 문자 영역을 분리하고, 이 중 선 성분을 벡터화하는 방법을 제안한다. 제안된 방법은 우선 이진화 및 세선화 과정에서의 데이터 손실을 방지하기 위해 스캔한 영상에 DRC 알고리즘을 적용한다. 그리고 영상의 기울어짐을 교정하기 위해 세선화된 영상에 허프 변환을 적용하여 기울어짐을 추정하고 교정한 다음, 서식의 구조를 이루는 선 성분을 추출해 낸다. 그리고 문자 영역은 연결 요소 분석법에 의해 문자 영역을 나타내는 데이터로 변환되며, 추출된 선 성분을 정렬, 합병 및 교정처리를 통해 벡터화 된다. 제안된 방법의 실효성을 입증하기 위해 각각 25명의 다른 사람이 필기구에 제한을 두지 않고 하나는 자를 사용하여 작성하고 다른 하나는 자를 사용하지 않고 작성한 서식에 대해 실험한 결과 전체 750개의 벡터 집합 중에서 전처리를 하지 않은 경우에는 666개, 전처리를 한 경우에는 746개의 서식 벡터 검출에 성공하여 그 유효성을 확인할 수 있었다.

• Annual Conference on Human and Language Technology
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• 1992.10a
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• pp.581-590
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• 1992

고품위 입출력 장치의 급속한 발달과 전자 출판 시스템의 출현은 더 다양한 서체를 요구하게 되었다. 컴퓨터에서 사용되고 있는 한글 서체는 명조, 고딕체를 제외하고는 주로 장식용 폰트를 만들어 사용하고 있다. 본 논문에서는 Cubic B-Spline 곡선을 이용하여 다양한 필기체 폰트를 구현하였고, 필기체가 가지는 특성(날림의 정도, 글자의 기울이기 정도, 각 음소의 크기, 각 글자의 크기의 균일성 등)에 따라 인자를 부여하여 개별화되고 사실적인 폰트를 생성하였다. 각 인자의 조합은 암호화되어 각 개인의 폰트로 부여된다. 즉, 개인의 고유 폰트는 폰트 암호(password)로 부여되고, 제어인자는 폰트암호의 해쉬값에 의해 선택되며, 사용자들로부터 이 제어인자들을 숨기게 되면 각 사용자들의 폰트는 유일하고, 안전하게 되므로, 일정정도의 안정성이 보장된다고 보여진다. 그리고 본 연구에서 구현된 폰트는 한글 필기체 문자인식의 정도를 측정하는 다양한 데이타를 제공하는 데에도 의미가 있다.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.546-550
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• 2010

In this paper, we propose a method for the postprocessing of cursive script recognition in Wine Label Images. The proposed method mainly consists of three steps: combination matrix generation, character combination filtering, string matching. Firstly, the combination matrix generation step detects all possible combinations from a recognition result for each of the pieces. Secondly, the unnecessary information in the combination matrix is removed by comparing with bigram of word in the lexicon. Finally, string matching step decides the identity of result as a best matched word in the lexicon based on the levenshtein distance. An experimental result shows that the recognition accuracy is 85.8%.

• Korean Journal of Cognitive Science
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• v.9 no.1
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• pp.1-11
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• 1998

In this paper, the features which are thought to be used by humans based on the psychological experiment of human information processing are applied to character recognition problem. Man will deal with a little large area information as well as pixel by pixel information. Therefore we define the feature that represents a little wide region I information called region feature, and combine the features derived from region feature and pixel by pixel features that have been used by now. The features we used are the result of region feature based preanalysis, mesh with region attributes, cross distance difference and gradient. The training and test data in the experiment are handwritten Korean alphabets, digits and English alphabets, which are trained on neural network using back propagation algorithm and recognition results are 90.27-93.25%, 98.00% and 79.73-85.75%, respectively Experimental results show that the feature we are suggesting in this paper is 1-2% better than UDLRH feature similar in attribute to region feature, and the tendency of misrecognition is more easily acceptable by humans.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.883-891
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• 1994

In this paper, we introduce new thinning algorithm which is useful for handwritten Korean character by using pixel directivity. At first, the directivity detection is performed before thinning. Each pixel is classified into the straight line of the oblique line based on its directivity. The algorithm using Rutovitz corossing number is applied to the straight line. And the algorithm using Hilditch crossing number is applied to the oblique line. The proposed algorithm is compared with six convention algorithms. Comparison criteria are similarity, noisy branch, and phoneme segmentation rate. Experiments with 570 characters have been conducted. Experimental result shows that the proposed algorithm is superior to six conventional algorithm with respect to similarity and phoneme segmentation rate.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.505-508
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• 2004

본 논문은 동적 3-D 뉴로 시스템(A Dynamic 3-D Neuro System)모델을 이용하여 오프라인 필기체 숫자 인식 실험을 하였다. 3-D 뉴로 시스템 모델을 사용함으로써 기존에 교육된 정보를 유지하면서 새로운 정보를 추가할 수 있는 추가학습이 가능했고, 동일한 범주의 정보에 대해서는 반복교육 횟수에 따라 교육정도가 점점 누적되는 반복교육이 가능했다. 교육과정을 통해 누적된 정보로부터 일반화된 패턴(Generalized Pattern)을 도출해 인식시 사용할 수 있었다. 패턴 인식기는 피드백루틴을 통해 미지의 입력이미지를 원형이미지로 복원한 후, 그 결과 데이터를 사용하여 문자를 인식하도록 동작한다. NIST의 MNIST 데이터베이스를 사용해 실험을 하였고, 결과로 $99.0\%$의 정인식률을 얻었다.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.297-307
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• 1999

A character recognition system, where a large amount of character images arrive continuously in real time, must preprocess character images very quickly. Moreover, information loss due to image trans-formations such as geometric normalization and thinning needs to be minimized especially when character images are small and noisy. Therefore, we suggest a prompt and effective feature extraction method without transforming original images. For this, boundary pixels are defined in terms of the degree in classification, and those boundary pixels are considered selectively in extracting features. The proposed method is tested by a handwritten character recognition and a car plate number recognition. The experiments show that the proposed method is effective in recognition compared to conventional methods. And an overall reduction of execution time is achieved by completing all the required processing by a single image scan.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.429-442
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• 2003

In this paper, we describe an address image recognition system for automatic processing of standard- size letter mail. The inputs to the system are gray-level mail piece images and the outputs are delivery point codes with which a delivery sequence of carrier can be generated. The system includes five main modules; destination address block location, text line separation, character segmentation, character recognition and finally address interpretation. The destination address block is extracted on the basis of experimental knowledge and the line separation and character segmentation is done through the analysis of connected components and vortical runs. For recognizing characters, we developed MLP-based recognizers and dynamical programming technique for interpretation. Since each module has been implemented in an independent way, the system has a benefit that the optimization of each module is relatively easy. We have done the experiment with live mail piece images directly sampled from mail sorting machine in Yuseong post office. The experimental results prove the feasibility of our system.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.64-73
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• 2000

The Korean character recognition technology for user interface in multimedia terminal requires fast processing time and high recognition rate. In this paper, we propose an phoneme and character recognition technology which uses characteristic information of korean and features of input strokes, i.e, feature point, feature vector, virtual vector, position relation between strokes. And, a recognition both phoneme and character by the various writing types of users uses korean database. The Korean database has been constructed by the characteristic information of korean and phoneme models which have various stroke information. Also, we use successive processing by the position relation between strokes and backtracking processing by the modification processing of stroke numbers which composed of each phoneme. This method reduces the complex processing of phoneme separation. The proposed on-line korean character recognition system has obtained 13msec average character processing time and correct recognition rate more than $95{\%}$ In a recognition experiment, where we tested 600 characters written by 10 people among 1,200 words.