• Journal of KIISE
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• v.43 no.2
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• pp.186-195
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• 2016

This paper proposes a vehicle license plate detection method in real road environments using 8 bit-MCT features and a landmark-based Adaboost method. The proposed method allows identification of the potential license plate region, and generates a saliency map that presents the license plate's location probability based on the Adaboost classification score. The candidate regions whose scores are higher than the given threshold are chosen from the saliency map. Each candidate region is adjusted by the local image variance and verified by the SVM and the histograms of the 8bit-MCT features. The proposed method achieves a detection accuracy of 85% from various road images in Korea and Europe.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.194-199
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• 2009

This paper proposes a face detection algorithm that uses geometrical information on face and hair region. This information that face adjoins hair regions can be the important one for face detection. It is also kept in images with frontal, rotated and lateral face. The face candidates are founded by the analysis of skin regions after detecting the skin and hair color regions in an image. Next, the intersected lesions between face candidates and hair's are created. Finally, the face candidates that include the subsets of these regions turn out to be face. Experimental results showed the high detection rates for frontal and lateral faces as well as faces geometrically distorted.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.273-282
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• 2006

In this paper, we propose index method introducing distance concept in word by a method weighting word. This index method is frequent representing an inquiry word and document index and compound noun or more than two adjoin nouns or noun phrase, the farther the distance between these nouns, the fewer selected ratio decreases in index point is the aiming, this choose guide word candidate by existent weight grant method and distance between candidates chose candidate finally in index within 3 sentences. Using in these way I document of 100 kinds of newspaper, scientific treatise, web document and so on, showed the correctness rate resulted of newspaper 92.03% scientific treatise 95% web document 73.33%.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.60-67
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• 2007

This research studies and analyzes the current trends and the frequency allocation bands for digital cordless phone(DCP) in other country. From these results, we propose 1.7GHz & 2.4GHz as a effective candidate frequency band for domestic DCP. A proposed 1.7GHz is expected to introduce DECT system of Europe. Therefore it is necessary to make an analysis of interference between 1.7GHz band and an adjacent IMT-2000 band. In this paper, we proposed the allocation of channel for 1.7GHz on the basis of the analysis of frequency interference between 1.7GHz band and an adjacent IMT-2000 band.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.10
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• pp.1005-1019
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• 2014

In this paper, we proposed the frequency candidates band for the spectrum sharing through researching and analyzing the current status of the policy and the economic values which is actively conducted on the United States and Europe. To this end, we investigated to the status and problems with the frequency reallocation and arrangement in respond to the current frequency demand. To solve these frequency reallocation and arrangement method problems, we introduce to the concept and current status of policy for the frequency method progress by advanced countries mainly. Also the results of the economic value analysis introduced in terms of the operators. In addition, we proposed the assessment terms and criteria for the selection of frequency candidates band through joint research and analysis results.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.309-314
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• 2010

In this paper, an intelligent security camera over internet is proposed. Among ISC methods, watersheds based methods produce a good performance in segmentation accuracy. But traditional watershed transform has been suffered from over-segmentation due to small local minima included in gradient image that is input to the watershed transform. And a zone face candidates of detection using skin-color model. last step, face to check at face of candidate location using SVM method. It is extract of wavelet transform coefficient to the zone face candidated. Therefore, it is likely that it is applicable to read world problem, such as object tracking, surveillance, and human computer interface application etc.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.347-348
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• 2018

일본 뇌염 바이러스(Japanese encephalitis virus)는 작은빨간집모기(Culex spp.)를 매개로 사람에게 감염될 수 있으며, 인체에 치명적인 질병을 유발한다. 일본 뇌염 바이러스의 혈청형(serotype)은 1종류이지만, 유전형(genotype)은 5종류(GI, GII, GIII, GIV, GV)로 분류되고 있다. 현재 일본 뇌염 바이러스 백신은 아시아 지역에서 감염 빈도가 높은 유전형 3(GIII)에 대한 백신이며, 사백신(inactivated vaccine)과 약독화 백신(attenuated vaccine)이 주로 사용되고 있다. 본 연구에서는 기존 백신의 부작용을 줄이고 한계점을 개선하기 위하여, 생물정보학 데이터베이스를 활용한 접근법을 통해 펩타이드 백신 후보군을 선별하였다. 5가지의 유전형 중에서도 감염 빈도가 가장 높은 유전형 3(GIII) 및 최근 감염빈도가 서서히 늘어나고 있어 주의가 요구되고 있는 유전형 1(GI)을 연구 대상으로 선정하였다. 여러 종류의 생물정보학 데이터베이스를 활용하여 백신으로 활용가치가 높은 것으로 보고되고 있는 외피 단백질(envelope protein)에 대한 아미노산 상동성을 분석하고, 이를 바탕으로 공통 적용이 가능한 동시에 면역원성이 높은 펩타이드 3종을 백신 후보군으로 선별하였다. 더 나아가 이들의 3차원 구조 모델링을 통해 보다 백신으로 활용 가능성이 높은 펩타이드를 최종 도출하였다.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.26-31
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• 2014

In this paper, we present performance analysis of video smoke detection based on BPN-Network that is using multi-smoke feature, and Neural Network. Conventional smoke detection method consist of simple or mixed functions using color, temporal, spatial characteristics. However, most of all, they don't consider the early fire conditions. In this paper, we analysis the smoke color and motion characteristics, and revised distinguish the candidate smoke region. Smoke diffusion, transparency and shape features are used for detection stage. Then it apply the BPN-Network (Back-Propagation Neural Network). The simulation results showed 91.31% accuracy and 2.62% of false detection rate.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.73-78
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• 2006

Conventional caption extraction methods use the difference between frames or color segmentation methods from the whole image. Because these methods depend heavily on heuristics, we should have a priori knowledge of the captions to be extracted. Also they are difficult to implement. In this paper, we propose a method that uses little heuristic and simplified algorithm. We use topographical features of characters to extract the character points and use MST(Minimum Spanning Tree) to extract the candidate regions for captions. Character regions are determined by testing several conditions and verifying those candidate regions. Experimental results show that the candidate region extraction rate is 100%, and the character region extraction rate is 98.2%. And then we can see the results that caption area in complex images is well extracted.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.494-499
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• 2012

In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.