• Title/Summary/Keyword: Automatic Information Extraction

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Improvement of contour extraction of pottery relics window area for automatic drawings extraction model (고배 유물 도면 자동 생성 모델의 투창 영역 윤곽선 검출 개선)

  • Kim, Dong-Joo;Ban, Sang-Woo
    • Annual Conference of KIPS
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    • 2019.10a
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    • pp.1098-1100
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    • 2019
  • 영상 처리를 기반으로 하는 발굴 유물(고배) 도면 자동 생성 모델의 성능향상을 위한 투창 영역 자동 검출과 투창 영역의 영상 정보의 특성을 반영한 윤곽선 검출을 통한 고배 유물 도면화 성능 향상 모델을 제안하고 실험결과를 통해 투창 영역의 윤곽선 정확도가 향상되었음을 보인다. 투창 영역은 형태적 특성상 고배 유물의 도면 자동 생성 과정에서 왜곡된 윤곽선 검출의 가능성이 높은 부분이어서 투창 영역 윤곽선의 정확도를 높이는 것이 중요한 요소이다.

Automatic Keyword Extraction using Hierarchical Graph Model Based on Word Co-occurrences (단어 동시출현관계로 구축한 계층적 그래프 모델을 활용한 자동 키워드 추출 방법)

  • Song, KwangHo;Kim, Yoo-Sung
    • Journal of KIISE
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    • v.44 no.5
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    • pp.522-536
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    • 2017
  • Keyword extraction can be utilized in text mining of massive documents for efficient extraction of subject or related words from the document. In this study, we proposed a hierarchical graph model based on the co-occurrence relationship, the intrinsic dependency relationship between words, and common sub-word in a single document. In addition, the enhanced TextRank algorithm that can reflect the influences of outgoing edges as well as those of incoming edges is proposed. Subsequently a novel keyword extraction scheme using the proposed hierarchical graph model and the enhanced TextRank algorithm is proposed to extract representative keywords from a single document. In the experiments, various evaluation methods were applied to the various subject documents in order to verify the accuracy and adaptability of the proposed scheme. As the results, the proposed scheme showed better performance than the previous schemes.

Skin Region Extraction Using Color Information and Skin-Color Model (컬러 정보와 피부색 모델을 이용한 피부 영역 검출)

  • Park, Sung-Wook;Park, Jong-Kwan;Park, Jong-Wook
    • 전자공학회논문지 IE
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    • v.45 no.4
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    • pp.60-67
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    • 2008
  • Skin color is a very important information for an automatic face recognition. In this paper, we proposed a skin region extraction method using color information and skin color model. We use the adaptive lighting compensation technique for improved performance of skin region extraction. Also, using an preprocessing filter, normally large areas of easily distinct non skin pixels, are eliminated from further processing. And we use the modified ST color space, where undesired effects are reduced and the skin color distribution fits better than others color space. Experimental results show that the proposed method has better performance than the conventional methods, and reduces processing time by $35{\sim}40%$ on average.

A Revised Dynamic ROI Coding Method Based On The Automatic ROI Extraction For Low Depth-of-Field JPEG2000 Images (낮은 피사계 심도 JPEG2000 이미지를 위한 자동 관심영역 추출기반의 개선된 동적 관심영역 코딩 방법)

  • Park, Jae-Heung;Kim, Hyun-Joo;Shim, Jong-Chae;Yoo, Chang-Yeul;Seo, Yeong-Geon;Kang, Ki-Jun
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.10
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    • pp.63-71
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    • 2009
  • In this study, we propose a revised dynamic ROI (Region-of-Interest) coding method in which the focused ROI is automatically extracted without help from users during the recovery process of low DOF (Depth-of-Field) JPEG2000 image. The proposed method creates edge mask information using high frequency sub-band data on a specific level in DWT (Discrete Wavelet Transform), and then identifies the edge code block for a high-speed ROI extraction. The algorithm scans the edge mask data in four directions by the unit of code block and identifies the edge code block simply and fastly using a edge threshold. As the results of experimentation applying for Implicit method, the proposed method showed the superiority in the side of speed and quality comparing to the existing methods.

Automatic Extraction of Hangul Stroke Element Using Faster R-CNN for Font Similarity (글꼴 유사도 판단을 위한 Faster R-CNN 기반 한글 글꼴 획 요소 자동 추출)

  • Jeon, Ja-Yeon;Park, Dong-Yeon;Lim, Seo-Young;Ji, Yeong-Seo;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.23 no.8
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    • pp.953-964
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    • 2020
  • Ever since media contents took over the world, the importance of typography has increased, and the influence of fonts has be n recognized. Nevertheless, the current Hangul font system is very poor and is provided passively, so it is practically impossible to understand and utilize all the shape characteristics of more than six thousand Hangul fonts. In this paper, the characteristics of Hangul font shapes were selected based on the Hangul structure of similar fonts. The stroke element detection training was performed by fine tuning Faster R-CNN Inception v2, one of the deep learning object detection models. We also propose a system that automatically extracts the stroke element characteristics from characters by introducing an automatic extraction algorithm. In comparison to the previous research which showed poor accuracy while using SVM(Support Vector Machine) and Sliding Window Algorithm, the proposed system in this paper has shown the result of 10 % accuracy to properly detect and extract stroke elements from various fonts. In conclusion, if the stroke element characteristics based on the Hangul structural information extracted through the system are used for similar classification, problems such as copyright will be solved in an era when typography's competitiveness becomes stronger, and an automated process will be provided to users for more convenience.

Automatic Extraction of Route Information from Road Sign Imagery

  • Youn, Junhee;Chong, Kyusoo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.6
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    • pp.595-603
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    • 2015
  • With the advances of the big-data process technology, acquiring the real-time information from the massive image data taken by a mobile device inside a vehicle will be possible in the near future. Among the information that can be found around the vehicle, the route information is needed for safe driving. In this study, the automatic extraction of route information from the road sign imagery was dealt with. The scope of the route information in this study included the route number, route type, and their relationship with the driving direction. For the recognition of the route number, the modified Tesseract OCR (Optical Character Recognition) engine was used after extracting the rectangular-road-sign area with the Freeman chain code tracing algorithm. The route types (expressway, highway, rural highway, and municipal road) are recognized using the proposed algorithms, which are acquired from colour space analysis. Those road signs provide information about the route number as well as the roads that may be encountered along the way. In this study, such information was called “OTW (on the way)” or “TTW (to the way)” which between the two should be indicated is determined using direction information. Finally, the route number is matched with the direction information. Experiments are carried out with the road sign imagery taken inside a car. As a result, route numbers, route number type, OTW or TTW are successfully recognized, however some errors occurred in the process of matching TTW number with the direction.

A Design of Important Sentence Extraction Method for Automatic Text Summarization System (자동 문서요약을 위한 중요문 추출 방법 설계)

  • Shin, Sung-Hyuk;Kim, Tae-Wan
    • Annual Conference of KIPS
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    • 2001.10a
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    • pp.543-546
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    • 2001
  • 본 논문에서는 빠른 속도로 증가하고 있는 인터넷상의 정보와 서비스를 검색함에 있어서 기본적인 내용은 유지하면서 정보의 과부하(information overload)문제를 해결하기 위한 문서요약의 방법으로 통계적 접근 방법에서 Kupiec의 요약문이 가지는 특성을 이용하여 문서의 방법을 설계하였다. 요약문의 각 문장에 대하여 중요도에 따라 가중치를 부여 한 후, 주어진 임계값에 따라 가중치가 낮은 문장들을 제외한다. 제외 후 가중치 점수를 부여해서 요약문 문장의 개수를 조절하면서 중요문을 추출할 수 있다.

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A Method of Descriptor Extraction for Automatic Document Clustering (자동 문서 클러스터링을 위한 디스크립터 추출 방안)

  • Yun, Bo-Hyun;Kang, Hyun-Kyu;Ko, Hyung-Dae
    • Annual Conference of KIPS
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    • 2000.04a
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    • pp.230-233
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    • 2000
  • 기존의 검색엔진은 검색결과를 적합도 순서로 나열하여 사용자가 원하는 문서를 찾는데 어려움이 있다. 이러한 문제의 해결책으로 검색결과 문서에 대해 자동 클러스터링을 수행하여 문서 내용이 유사한 문서가 하나의 클러스터내에 존재하도록 한다. 본 논문에서는 검색 결과 문서의 클러스터링에서 필요한 디스크립터 추출 방안을 제안한다. 각 클러스터 내에서 디스크립터를 추출하기 위해 정보검색의 색인과정에서 사용하는 용어 가중치 계산 방법을 이용한다.

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Nucleus Recognition of Uterine Cervical Pap-Smears using FCM Clustering Algorithm

  • Kim, Kwang-Baek
    • Journal of information and communication convergence engineering
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    • v.6 no.1
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    • pp.94-99
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    • 2008
  • Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the HSI model. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The fuzzy C-means clustering algorithm is employed to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.

Linear System Depth Detection using Retro Reflector for Automatic Vision Inspection System (자동 표면 결함검사 시스템에서 Retro 광학계를 이용한 3D 깊이정보 측정방법)

  • Joo, Young Bok
    • Journal of the Semiconductor & Display Technology
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    • v.21 no.4
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    • pp.77-80
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    • 2022
  • Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. It has been populated because of the accuracy and consistency in terms of QC (Quality Control) of inspection processes. Also, it is important to predict the performance of an AVI to meet customer's specification in advance. AVI are usually suffered from false negative and positives. It can be overcome by providing extra information such as 3D depth information. Stereo vision processing has been popular for depth extraction of the 3D images from 2D images. However, stereo vision methods usually take long time to process. In this paper, retro optical system using reflectors is proposed and experimented to overcome the problem. The optical system extracts the depth without special SW processes. The vision sensor and optical components such as illumination and depth detecting module are integrated as a unit. The depth information can be extracted on real-time basis and utilized and can improve the performance of an AVI system.