• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권7호
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.

• 한국정보통신학회논문지
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• 제9권8호
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• pp.1821-1827
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• 2005

현재 유선 인터넷 환경에서는 이미지를 표현하기 위하여 대부분 GIF와 JPG를 이용하며, 무선 인터넷 환경에서는 SVG, wBMP, SIS, PNG, Flash Lite 등과 같은 다양한 이미지 파일들을 이용한다. 따라서 유${\cdot}$무선인터넷을 동시에 지원하기 위한 콘텐츠를 제작하는 경우 이중으로 제작비용이 소요되는 문제점이 있다. 이에 본 논문에서는 유무선 인터넷을 동시에 지원할 수 있는 서비스를 재발할 때, SVG를 효율적으로 적용하는 방법을 제안하였다. 유${\cdot}$무선 인터넷을 동시에 지원하는 서비스에 SVG를 이용함으로써 유${\cdot}$무선 인터넷 기반의 콘텐츠를 제작할 때 기업이 지출해야 하는 개발비용을 크게 줄일 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.3121-3144
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• 2023

As interest in the metaverse has grown, there has been a demand for avatars that can represent individual users. Consequently, research has been conducted to reduce the time and cost required for the current 3D human modeling process. However, the recent automatic generation of 3D humans has been focused on creating avatars with a realistic human form. Furthermore, the existing methods have limitations in generating avatars with imbalanced or unrealistic body shapes, and their utilization is limited due to the absence of datasets. Therefore, this paper proposes a new framework for automatically transforming and creating stylized 3D avatars. Our research presents a definitional approach and methodology for creating non-realistic character avatars, in contrast to previous studies that focused on creating realistic humans. We define a new shape representation parameter and use a deep learning-based method to extract character body information and perform automatic template mesh transformation, thereby obtaining non-realistic or unbalanced human meshes. We present the resulting outputs visually, conducting user evaluations to demonstrate the effectiveness of our proposed method. Our approach provides an automatic mesh transformation method tailored to the growing demand for avatars of various body types and extends the existing method to the 3D cartoon stylized avatar domain.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권8호
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• pp.586-590
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• 2009

본 논문의 목적은 P2P 네트워크 상에서 동적 환경 애플리케이션을 지원하기 위한 MapReduce 의 설계이다. MapReduce는 클라우드컴퓨팅 중에서 대용량 데이터의 병렬처리를 위해서 개발된 소프트웨어 프레임워크이다. P2P 기반 네트워크의 특징은 노드 고장이 언제든지 발생할 수 있으며, 이런 노드 고장을 제어하기 위해 Pastry라는 DHT 라우팅 프로토콜의 사용에 초점을 맞추었다. 본 논문의 결과는 프레임워크가 양호한 계산 효율과 확장성을 유지하는 가운데 P2P 네트워크 시스템의 다양한 애플리케이션에 적용될 수 있음을 보이고 있다. 향후 몇 년 동안은 P2P 네트워크와 병렬 컴퓨팅이 산업과 학계에서 매우 중요한 연구 및 개발 주제로 자리 잡을 것으로 확신한다.

• 전자공학회논문지B
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• 제31B권1호
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• pp.99-106
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• 1994

In this paper, we develop an algorithm which recognizes Ilpa-style shorthand characters by on-line. It discriminates the structure of characters using coordinates which are measured by tablet board, then it outputs the recognized characters using the fuzzy inference rules. Shorthand characters have several forms, in which an initial or a middle sound depends on angle and length while a last sound is treated as a hook. We apply fuzzy inference rules to the discrimination of the length, the angle, the curve, and the straight line. We also built up a set of standard character codes in order to reduce the processing time.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.900-904
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• 1991

In this paper, our study for the recognition of Hand-written Korean characters, Arabic numbers and alphabets by neural netwoks. This System extracts feature of character by using the MESH feature point of handwritten character, Arabic numbers and alphabets. To reduce the input image data, features are extracted from each input images. A MLP(multi-layer perceptron) with one hidden layer was trained with a modified BEP(back error propagation) algorithm. This method extracts feature sets of the characters directly from the scanner and can enhance computation speed without using the special preprocesses such as size normalization, smoothing, and thinning.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.745-748
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• 1998

Recently, image and voice processing part is using wavelet transform. We propose thining algorithm using wavelet tranform. Wavelet transform consists of low frequency and high frequency in the spatial and frequency domain. After the wavelet decomposition, more than 90 percents of energy are contained in lowest frequency band. Therefor, for images with large difference of gray value between foreground and background like character images, we can more accurately in the lowest frequency band. Lowest frequency band has wavelet transform significant coefficient(WTS) that is required for the thinning algorithm we proposed Paper [3][5][7][8] can not separate consonants and vowels of korean characters. Becuase korean characters have structural feature. This paper can separate consonants and vowels. Simulation executed low frequency image and data compression can reduce 1/4$^{n}$ with level n. we can redcue time complexity 3/8.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.466-468
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• 2005

MMORPG enables thousands of players to play in an evolving virtual world at the same time over the internet. So, the load of this kind of games is heavier than that of any other precedents. One of load balancing methods is map-partition to divide the load of entire system which is vulnerable to delay message between clients and servers. In this paper, we propose a game architecture using MigAgent to help migration of player character between field servers and to reduce message traffic between clients and field servers.

• 전자공학회논문지B
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• 제30B권6호
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• pp.76-85
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• 1993

In this paper, we propose a stroke matching method for the off-line recognition of handprinted Hangul. In this method, the preprocessing steps such as position normalization, contour tracing and thinning are carried out first. Then, after extracting features such as the firection component distribution of contour, the direction component distribution of skeleton, and the distribution of structural feature points, strokes are extracted and matched based on the midpont distribution of the direction and the length of each stroke. In order to reduce the recognition time, a preliminary classification based on the direction component distribution features of the contour is performed. In order to domonstrate the performance of the proposed method, experiments with 520 most frequently used Hangul were performed, and 90.7% of correct recognition rate and 0.46second of recognition time per one character has been obtained. This results reveal that the proposed method can absorb effectively the noise in input character and the variations of stroke slant.

• 한국정보과학회논문지:시스템및이론
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• 제33권10호
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• pp.759-767
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• 2006

컴퓨터 그래픽스 분야에 활용되는 단순화 기법(LoD)은 실시간 렌더링을 위해 메쉬(mesh)의 다각형 수를 줄이는 방법으로 널리 알려져 있다. 본 논문에서는 이러한 단순화 기법의 기본적인 개념이 가상 캐릭터의 동작 단순화에 적용된 새로운 방법론을 제안한다. 가상 캐릭터의 구성요소 중 하나인 관절은 동작을 생성하는 기본 단위로서 메쉬와 연계되어 캐릭터의 움직임을 생성한다. 동작 단순화의 기본과정은 이러한 캐릭터의 관절 수를 줄이고 남은 관절들의 움직임을 기존동작과 가장 유사하도록 최적화 하는 방법이다. 동작의 최적화를 위해 기존 동작과 단순화 된 동작 간의 오차를 측정하는 방법론을 제시하고, 최적화 문제를 빠르게 풀기 위해 동작 간 오차 식을 선형시스템으로 재구성한다. 본 논문에 제시한 동작 단순화 방법은 동작편집 또는 군중 애니메이션의 성능향상 둥 캐릭터 애니메이션의 여러 분야에 유용하게 활용 될 수 있다.