• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.33-36
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• 2003

Principal component analysis (PCA) was used to improve image classification by the unsupervised classification techniques, the K-means. To do this, I selected a Landsat TM scene of Jeju Island, Korea and proposed two methods for PCA： unstandardized PCA (UPCA) and standardized PCA (SPCA). The estimated accuracy of the image classification of Jeju area was computed by error matrix. The error matrix was derived from three unsupervised classification methods. Error matrices indicated that classifications done on the first three principal components for UPCA and SPCA of the scene were more accurate than those done on the seven bands of TM data and that also the results of UPCA and SPCA were better than those of the raw Landsat TM data. The classification of TM data by the K-means algorithm was particularly poor at distinguishing different land covers on the island. From the classification results, we also found that the principal component based classifications had characteristics independent of the unsupervised techniques (numerical algorithms) while the TM data based classifications were very dependent upon the techniques. This means that PCA data has uniform characteristics for image classification that are less affected by choice of classification scheme. In the results, we also found that UPCA results are better than SPCA since UPCA has wider range of digital number of an image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.184-185
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• 2022

인터넷 환경의 변화에 따라 텍스트 기반의 정보 전달에서 멀티미디어 기반의 스트리밍 방식으로 바뀌어가고 있다. 또한 대용량의 동영상 데이터뿐 아니라 Shorts, Clip Reels 또는 등 다양한 방식의 동영상 형태로 배포되고 있으며 서비스 플랫폼에서는 손쉽게 편집할 수 있도록 기능을 제공하고 있다. 대용량 콘텐츠, TV, Youtue 콘텐츠를 포함하여 소용량 동영상 편집에 필요한 영상 제작 기술에서 가장 인력과 시간이 많이 소요되는 부분은 편집 단계로 딥러닝 기반 인공지능 기술을 활용하여 자동화하고 있으며 영상편집에서 가장 기본이 되는 단위인 씬검출 기법을 개발하였다. 키프레임 검출 기법과 유사도 기법을 이용하여 씬을 추출하였으며 블록 Cost Function을 이용하여 최적화하여 0.5214의 정확도를 도출하였다.

• Smart Media Journal
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• v.1 no.4
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• pp.27-34
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• 2012

In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

• Language and Information
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• v.20 no.1
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• pp.1-24
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• 2016

Korean is well-known for its topic-prominent properties. In this paper, we look into several subtypes of topic constructions whose grammatical complexities have received much attention in generative grammar. From a semantic/pragmatic view, topics in Korean can be classified into three different types: aboutness, contrastive, and scene-setting. Meanwhile, syntax can classify topic constructions into two types, depending on whether or not the comment clause following topic has a syntactic gap linked to the topic. In this paper, we review some key properties of these topic constructions in Korean, and suggest that each type is licensed by tight interactions between syntactic and semantic constraints. In particular, the paper tries to offer a Construction Grammar analysis where each grammatical component is interacting in non-modular ways and in which the multiple inheritance network of constructions plays an important role in capturing cross-cutting generalizations of the topic constructions.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.181-187
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• 2013

When there are background noises or some people speaking at the same time, a human's auditory sense has the ability to listen the target speech signal with a specific purpose through Auditory Scene Analysis. The CASA system with human's auditory faculty system is able to segregate the speech. However, the performance of CASA system is reduced when the CASA system fails to determine the correct position of the speech. In order to correct the error in locating the speech on the CASA system, voice activity detection algorithm is proposed in this paper, which is a combined auditory scene analysis with PAR(Periodic to Aperiodic component Ratio). The experiments have been conducted to evaluate the performance of voice activity detection in environments of white noise and car noise with the change of SNR 15~0dB. In this paper, by comparing the existing algorithms (Pitch and Guoning Hu) with the proposed algorithm, the accuracy of the voice activity detection performance has been improved as the following: improvement of maximum 4% at SNR 15dB and maximum 34% at SNR 0dB for white noise and car noise, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.28-33
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• 2003

This paper proposes a database index and retrieval method using the PCA(Principal Component Analysis). We perform a scene change detection and key frame extraction from the DC Image constructed by DCT DC coefficients in the compressed video stream that is video compression standard such as MPEG. In the extracted key frame, we use the PCA, then we can make codebook that has a statistical data as a codeword, which is saved as a database index. We also provide retrieval image that are similar to user's query image in a video database. As a result of experiments, we confirmed that the proposed method clearly showed superior performance in video retrieval and reduced computation time and memory space.

• Proceedings of the Korean Institute of Landscape Architecture Conference
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• 2007.10b
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• pp.72-77
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• 2007

Civic participation in managing the work of a park is a natural experience, and urban culture has a role in forming and communicating ideas. However, when it comes to managing a copse, there is no clear scenic image. In this study, my intention was to determine a desirable scene involving a copse and suggest a target image for managing work from a scenic perspective. I selected 12 photographs and listed 10 pairs of adjectives that were judged to reflect the effect produced by the copse scene using the repertory grid development technique. In addition, I performed a scenic evaluation using the semantic differential(SD) method with each pair of adjectives. Factor analysis was performed based on questionnaire survey results, such that the scenic structure of the copse had a clear definition. In addition, the physical characteristics of the photographs were analyzed using Adobe Photoshop 6.0 and the correlations between the results of the questionnaire survey were understood using multiple regression analysis. A desirable scenic image of the copse became clear through this process and I was able to suggest various options of scenic images. Taking the aspects of urban culture into consideration, park improvement projects(including their planning stages) should be implemented by involving residents, which will lead to further development of park planning and maintenance theories and projects giving due consideration to residents' opinions.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.470-472
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• 1999

Sparse coding은 최소한의 active한 (non-orthogonal) basis vector를 이용하여 데이터를 표시하는 하나의 방법이다. Sparse coding에서 basis coefficient들이 statistically independent 하다는 constraint를 주기에 sparse coding은 independent component analysis(ICA)와 밀접한 관계를 가지고 있다. 본 논문에서는 sparse representation을 위하여 super-Gaussian prior를 이용한 ICA, 즉 sparse ICA 방법을 제시한다. Sparse ICA 방법을 이용하여 natural scenes의 basis vector를 찾고 이와 sparse coding과의 관계를 고찰한다. 여러 가지 super-Gaussian prior들을 고려하지 않고 이들이 ICA에 미치는 영향에 대해 살펴본다.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1158-1159
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• 2009

Tri-stimulus values of CIE-XYZ and RGB values obtained by photographic film, CCD camera or scanner depend on the spectral sensitivity of imaging devices and the spectral radiant distribution of the illumination. It is important to record and reproduce the reflectance spectra of the object for true device independent color reproduction and high accurate recording of the scene. In this paper, a method to record the reflection spectra of the object is introduced and its application to spectral endoscopes is presented.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2130-2131
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• 2011

Electric fire breaks out by various causes such as electric short, overload(over current), leakage current, poor contact, static electricity, insulation deterioration, partial disconnection and etc. In this paper, we studied analysis technique for scientific and systematic judgment for distinction of electricity fire existence and nonexistence, and described about electricity fire cause analysis process for collecting physical evidences. We handled external form analysis, Substance extension analysis, X-ray transmission analysis, cross-section analysis, thermal analysis, chemical structure analysis, surface structure analysis, component analysis, electrical properties analysis, and circuit analysis by analysis technique for electricity fire cause judgment. We expect that analysis technic elevation and correct cause of fire analysis of scene of a fire investigators and analysts through this paper which see help.