• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.37-44
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• 2006

In this paper, a new version of the ICM method(MICM, modified ICM) in which the contextual information is modelled by Markov random fields (MRF) is introduced. To extract the feature, a new local MRF model with a fitting block neighbourhood is proposed. This model selects contextual information not only from the relative intensity levels but also from the geometrically directional position of neighbouring cliques. Feature extraction depends on each block's contribution to the local variance. They discriminates it into several regions, for example context and background. Boundaries between these regions are also distinctive. The proposed algerian performs segmentation using directional block fitting procedure which confines merging to spatially adjacent elements and generates a partition such that pixels in unified cluster have a homogeneous intensity level. From experiment with ink rubbed copy images(Takbon, 拓本), this method is determined to be quite effective for feature identification. In particular, the new algorithm preserves the details of the images well without over- and under-smoothing problem occurring in general iterated conditional modes (ICM). And also, it may be noted that this method is applicable to the handwriting recognition.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.610-617
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• 2003

Similarity matching in video database is of growing importance in many new applications such as video clustering and digital video libraries. In order to provide efficient access to relevant data in large databases, there have been many research efforts in video indexing with diverse spatial and temporal features. however, most of the previous works relied on sequential matching methods or memory-based inverted file techniques, thus making them unsuitable for a large volume of video databases. In order to resolve this problem, this paper proposes an effective and scalable indexing technique using a trie, originally proposed for string matching, as an index structure. For building an index, we convert each frame into a symbol sequence using a window order heuristic and build a disk-resident trie from a set of symbol sequences. For query processing, we perform a depth-first search on the trie and execute a temporal segmentation. To verify the superiority of our approach, we perform several experiments with real and synthetic data sets. The results reveal that our approach consistently outperforms the sequential scan method, and the performance gain is maintained even with a large volume of video databases.

• 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%.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.532-534
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• 2005

본 논문은 자동적인 언어기반자원구축을 위해 신문 말뭉치에서 괄호를 이용하여 추출한 대역어쌍들을 군집화하고 각 군집에서 적합대역어를 선정하는 방법을 제안한다. 기존 연구에서 주로 제시된 음차표기어 대역쌍 추출 방법은 완전한 형태의 영어원어 자소 정보를 이용하기 때문에 약어는 고려대상에서 제외되었다. 그러나 약어형태의 영어원어가 신문에서는 약 $82\%$를 차지하기 때문에 이를 처리할 방법이 필요하다. 따라서 본 논문에서는 바이그램을 기본으로 하는 형태정보를 이용하여 적합대역어를 선정하고 이와 형태정보를 공유하는 한국어대역어쌍들을 군집화한다. 또한, 음차표기어와 두문자어에 대한 처리를 추가하여 적용범위를 넓힌다. 실험을 위하여 신문말뭉치에서 추출한 대역어쌍 1,806개 중 영어원어를 기준으로 한국어대역어의 수가 5개 이상인 대역어쌍 집합 200개를 선정하였다. 본 논문에서 제시한 방법으로 측정한 결과, 대역어 군집화에 대해서는 $74\%$의 정확율과 $65\%$의 재현율을, 적합대역어 선정에 대해서는 $97\%$의 정확율을 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.57-60
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• 2020

순위다중패턴매칭문제는 길이가 n인 텍스트 T와 패턴들의 집합 P' = {P₁,P₂…,P_k}가 주어졌을 때, P'에 속하는 패턴들과 상대적인 순위가 일치하는 T의 모든 부분문자열들의 위치를 찾는 문제이다. P'에서 가장 짧은 패턴의 길이가 m, 가장 긴 패턴의 길이를 $\bar{m}$, 모든 패턴들의 길이의 합을 M, q개의 연속된 문자들을 q-그램이라 할 때, 기존에 텍스트의 핑거프린트를 이용하여 순위다중패턴매칭문제를 $O(q!+nqlogq+Mlog\bar{m}+nM)$ 시간에 해결하는 알고리즘이 제시되었다. 본 논문에서는 텍스트의 핑거프린트를 활용하여 O(max(q!,M,n))개의 스레드를 이용하여 순위다중패턴매칭문제를 평균적으로 $O(\bar{m}+qlogq+n/q!)$ 시간에 해결하는 병렬 구현 방법을 제시한다. 실험 결과, n = 1,000,000, k = 1,000, m = 5, q = 3일 때, 본 논문에서 제시하는 병렬 구현 방법은 기존의 순차 알고리즘보다 약 19.8배 빠르게 수행되었다.

• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.453-460
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• 2007

In this paper, we present a method to extract the text lines in poorly structured documents. The text lines may have different orientations, considerably curved shapes, and there are possibly a few wide inter-word gaps in a text line. Those text lines can be found in posters, blocks of addresses, artistic documents. Our method based on the traditional perceptual grouping but we develop novel solutions to overcome the problems of insufficient seed points and vaned orientations un a single line. In this paper, we assume that text lines contained tone connected components, in which each connected components is a set of black pixels within a letter, or some touched letters. In our scheme, the connected components closer than an iteratively incremented threshold will make together a chain. Elongate chains are identified as the seed chains of lines. Then the seed chains are extended to the left and the right regarding the local orientations. The local orientations will be reevaluated at each side of the chains when it is extended. By this process, all text lines are finally constructed. The proposed method is good for extraction of the considerably curved text lines from logos and slogans in our experiment; 98% and 94% for the straight-line extraction and the curved-line extraction, respectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.56-61
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• 2022

In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.63-68
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• 2010

Recently, to accelerate the Ubiquitous generation, the input interface of the mobile machinery and tools are actively being researched. In addition with the existing interfaces such as the keyboard and curser (mouse), other subdivisions including the handwriting, voice, vision, and touch are under research for new interfaces. Especially in the case of small-sized mobile machinery and tools, there is a increasing need for an efficient input interface despite the small screens. This is because, additional installment of other devices are strictly limited due to its size. Previous studies on handwriting recognition have generally been based on either two-dimensional images or algorithms which identify handwritten data inserted through vectors. Futhermore, previous studies have only focused on how to enhance the accuracy of the handwriting recognition algorithms. However, a problem arisen is that when an actual handwriting is inserted, the user must select the classification of their characters (e.g Upper or lower case English, Hangul - Korean alphabet, numbers). To solve the given problem, the current study presents a system which distinguishes different languages by analyzing the form/shape of inserted handwritten characters. The proposed technique has treated the handwritten data as sets of vector units. By analyzing the correlation and directivity of each vector units, a more efficient language distinguishing system has been made possible.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.305-310
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• 2010

In this paper, we propose a heuristic algorithm for motion correspondence based on a point series similarity. A point series is a sequence of points which are sorted in the ascending order of their x-coordinate values. The proposed algorithm clusters the points of a previous frame based on their local adjacency. For each group, we construct several potential point series by permuting the points in it, each of which is compared to the point series of the following frame in order to match the set of points through their similarity based on a proximity constraint. The longest common subsequence between two point series is used as global information to resolve the local ambiguity. Experimental results show an accuracy of more than 90% on two image sequences from the PETS 2009 and the CAVIAR data sets.

• Communications of Mathematical Education
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• v.14
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• pp.197-215
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• 2001

최근 수학적 사고력 연구가 구체적 수학내용에 기반한 활동과 조작에 대한 연구보다는 활동이나 조작을 통한 결과로 수학적 사고력에 접근하는 일회성 연구로 이루어지는 경향이 있다. 본고에서는 교육 내용을 선정하기 위해 학교수학에서 아동들이 어떤 수학적 사고를 하는데 장애을 겪는지에 주목하여, 이러한 장애를 극복하는 것을 통해 수학적 사고력의 신장을 생각해보고자 하였다. 이에 대수에서는 문자도입에 따른 추상적 상징의 수용과 이용부분에서, 기하에서는 논증기하의 증명도입과정에서 형식적, 연역적 사고 시작으로 아동이 수학적 사고에 어려움을 겪는다는 사살에 주목하였다. 특히 논증 기하의 연역적, 형식적 증명은 논리와 추론이 바탕이 되어야 한다. 그런데 논리와 추론은 고등학교 1학년과정 집합과 명제부분에 들어있어 아동은 논리와 추론에 대한 어떤 경험도, 교육도 받지 않은 상태에서 증명을 하게 된다. 이에 교육 내용으로 수학적 사고력을 신장을 위해 가장 필요한 내용이 논증 기하가 도입되기 이전에 초등학교 5,6학년 아동을 대상으로한 논리와 추론교육이라고 본다. 또한 교육 방법으로는 컴퓨터를 이용한 교육공학적 접근을 하고자 하였다. 교육공학적 접근이 적극 권장되는 교육적 현실과 정규교육과정에서 이를 받아들일만한 시간적 여유가 없음을 감안하여, 교과 내용과 연계된 컴퓨터 교육을 제안하는 바이다. 이에 논리 및 추론 교육은 컴퓨터 교육으로 초등학교의 특기적성 시간이나 정규수업 시간에 이용할 것을 제안한다. 논리와 추론교육을 위해 무엇을 어떻게 가르칠 것인가에 대한 답으로 논리와 추론교육에 적합한 수학적 내용으로 크게 이산수학과 중등 기하의 초등화하여 탐구하도록 하는 내용을, 교육 방법 측면에서는 논리와 추론 교육을 위한 LOGO 기반 마이크로월드를 설계, 이용하여 수학적 사고력을 신장시키고자 한다. 여기까지가 수학적 사고력을 위한 가능성을 모색한 것이라면 후속연구로 이러한 가능성을 실험연구로 검증하고자 한다.