• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.721-723
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• 2007

Recently, the size and location of the acquired container image while the container is loading and unloading in Harbors is not fixed. And it is difficult to get a good image for recognition because of the variation of external environment as those the size of container and where the yard-tractor stop is. In this paper, we estimate where the container ISO-code set is using Top-hat transform from realtime images and get an image to recognize container ISO-code using PAN/TILT/ZOOM camera. We extract the container ISO-code using Top-hat transform and Histogram projection. After binarization, we extract each character from complex background using labeling. We use BP(Backpropagation Network) to recognize extracted characters.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.3
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• pp.1-14
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• 2009

In this paper, we propose a feature vector and its applying method which can be utilized for the extraction of the car license plate region. The proposed feature vector is extracted from direction code histogram of edge direction of gradient vector of image. The feature vector extracted is forwarded to the MLP classifier which identifies character and garbage and then the recognition of the numeral and the location of the license plate region are performed. The experimental results show that the proposed methods are properly applied to the identification of character and garbage, the rough location of license plate, and the recognition of numeral in license plate region.

• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.19-26
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• 2022

This paper presents a pre-processing method to facilitate the container's BIC-code recognition. We propose a network that can find ROI(Region Of Interests) containing a BIC-code region and estimate a homography matrix for warping. Taking the structure of STN(Spatial Transformer Networks), the proposed network consists of next 3 steps, ROI detection, homography matrix estimation, and warping using the homography estimated in the previous step. It contributes to improving the accuracy of BIC-code recognition by estimating ROI and matrix using the proposed network and correcting perspective distortion of ROI using the estimated matrix. For performance evaluation, five evaluators evaluated the output image as a perfect score of 5 and received an average of 4.25 points, and when visually checked, 224 out of 312 photos are accurately and perfectly corrected, containing ROI.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1515-1524
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• 2008

This paper proposes a method that detects a license plate in complex background using a multiple-color model and character layout information. A layout of a green license plate is different from that of a white license plate. So, this study used a strategy that firstly assumes the plate color and then utilizes its layout information. At first, it extracts green areas from an input image using a multiple-color model which combined HIS and YIQ color models with RGB color model. If green areas are detected, it searches the character layout of the green plate by analyzing the connected components in each areas. If not detected, it searches the character layout of the white plate in all area. Finally, it extracts a license plate by grouping the connected components which corresponds to characters. Experimental result shows that 98.1% of 419 input images are correctly detected. It also shows that the proposed method is robust against illumination, shadow, and weather condition.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.17-24
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• 2005

In this paper, we will show that a control search methodology is a alternative method of a sequential search which is difficult in finding books for arrangement at library or a bookstore when books are out of place. To solve the problem of the sequential search, we apply a edge operator and the Hough Transform to boundary of a taken photograph image book. We generate histogram by a projected image from boundary range of selected books and select title areas from this and possible areas which are a character number of title, authors, a publishing company and an array sequence. Finally, we can select the final possible area of a book location by a curve fitting and a regression line extraction, and show utility through experiment.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.19-26
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• 2013

In the Malaysian license plates, alphabets and numerals which are made by plastic, are adhered to a frame as embossing style and occasionally characters in horizontal, vertical directions are aligned with narrow space. So the extraction of character stroke information can be hard in the vehicle images of low illumination intensity. In this paper, Malaysian license plate recognition algorithm for low illumination intensity image is proposed. DoG filtering based character stroke generation method is introduced to derive exact connected components of strokes in the vehicle image of low illumination intensity. After localization of plate by connected component analysis, characters are segmented and recognized. Algorithm is experimented for the 6,046 vehicle images captured in Kuala Lumpur by IR camera without using any special light during day and night. The experimental results show that recognition accuracy of plates is 96.1%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.93-100
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• 2007

In this paper, a novel approach based on wavelet transform is proposed to process the scraped character which is represented on digital image. The basis idea is that the scraped character is described by its textured neighborhood, and it is decomposed into multiresolution features at different levels with its background region. The image is first decomposed into sub bands by applying Daubechies wavelets. Character features are extracted from the low frequency sub-bands by partition, FCM clustering and area-based region process. High frequency ones are activated by applying local energy density over a moving mask. Features are synthesized in order to reconstruct the original image state through inverse wavelet transform Background region is eliminated and character is extracted. The experimental results demonstrate the effectiveness of the proposed method.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2005.05a
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• pp.273-277
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• 2005

본 연구는 한국어 어말어미 산출시 나타나는 대뇌 활성화 영역을 살펴보기 위하여 실시되었다. 두 가지 실험이 실시되었다 실험 1은 어말어미의 기본형을 주고 이를 의문형, 명령형으로 산출하는 고립단어 실험을 실시하였다. 통제 조건으로 모음변환조건(C1)과 아라비아문자보기(C2)를 사용하였다. 실험 1의 결과 ‘어말어미-C1’ 조건에서 좌반구의 측두엽과 전두엽부분의 의 활성화 superior temporal gyrus와 inferior frontal gyrus의 활성화가 관찰되었다. ‘어말어미-C2’ 의 조건에서 우반구에서 후두엽의 활성화와 좌반구에서의 후두엽, 전두엽, lingual G, Cuneus, fusiform G, inferior occipital G에서의 활성화를 관찰할 수 있었다. 실험 2는 명령형과 의문형 어미의 형태점화효과와 관련된 대뇌 활성화 영역을 관찰하기 위하여 Er-fMRI 기법을 이용하여 실시되었다. 실험 조건은 어미동일조건, 어간반복조건, 무관련 조건으로 구성되었다. 피험자들은 점화자극이 제시된 후 신호가 제시되고 나오는 표적단어를 의문형 또는 명령으로 산출하도록 하는 과제를 실시하였다. 뇌 활성화 영역을 분석한 결과 의문형과 명령형을 산출할 때의 활성화 영역에서 $^{\ast}^{\ast}^{\ast}$를 볼 때의 영역을 빼기 (substraction)한 결과 공통적으로 좌반구 브로카 영역이 활성화되었고, 의문형과 명령형 안에서 어미동일조건에서 무관련 조건을 뺀 경우에는 좌반구의 superior temporal G 영역의 활성화가 관찰되었다. 이들 결과를 종합해 볼 때 어말어미 산출 그 자체와 직접 관련되는 영역으로는 좌반구의 측두엽과 전두엽 부분이 관찰되었다. 특히 한국어 어말어미 산출시 나타나는 형태점화 양상과 관련된 대뇌영역으로 발견된 브로카 영역에서의 활성화는 어미 변환과 관련된 영역이라기보다는 산출시 관련되는 articulation, motor coordinate관련 영역으로 추정되고, 측두엽의 활성화는 형태소, 의미 관련 지식의 data base로 추정된다. 또한 우반구 전두엽 부분에서 관찰된 활성화는 억제관련 영역으로 짐작된다.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.183-189
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• 2002

In this paper, we propose an algorithm to extract the E-mail address in calling card images. Firstly, text regions are separated from background. in the image. To do this, the properties of e-mail addresses and the texture features in the image is used. And then, each text region is explored to find the candidates of e-mail region. Finally, each candidate is divided into characters to find at-symbol(@), that is, e-mail region. The experimental results show hit-ratio over 93.3％ for the various kind of calling cards containing different fonts, background images, caricatures.