• Title/Summary/Keyword: 자동정보 추출

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A Study on High-Speed Extraction of Bar Code Region for Parcel Automatic Identification (소포 자동식별을 위한 바코드 관심영역 고속 추출에 관한 연구)

  • Park, Moon-Sung;Kim, Jin-Suk;Kim, Hye-Kyu;Jung, Hoe-Kyung
    • The KIPS Transactions:PartD
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    • v.9D no.5
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    • pp.915-924
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    • 2002
  • Conventional Systems for parcel sorting consist of two sequences as loading the parcel into conveyor belt system and post-code input. Using bar code information, the parcels to be recorded and managed are recognized. This paper describes a 32 $\times$ 32 sized mini-block inspection to extract bar code Region of Interest (ROI) from the line Charged Coupled Device (CCD) camera capturing image of moving parcel at 2m/sec speed. Firstly, the Min-Max distribution of the mini-block has been applied to discard the background of parcel and region of conveying belts from the image. Secondly, the diagonal inspection has been used for the extraction of letters and bar code region. Five horizontal line scanning detects the number of edges and sizes and ROI has been acquired from the detection. The wrong detected area has been deleted by the comparison of group size from labeling processes. To correct excluded bar code region in mini-block processes and for analysis of bar code information, the extracted ROI 8 boundary points and decline distribution have been used with central axis line adjustment. The ROI extraction and central axis creation have become enable within 60~80msec, and the accuracy has been accomplished over 99.44 percentage.

Study for social relationship extraction for automatically image tagging in Folksonomy (폭소노미에서 이미지 자동 태깅을 위한 사회적 관계 추출에 관한 연구)

  • Eom, Wonyong;Lee, Sihyoung;Ro, Yong Man
    • Annual Conference of KIPS
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    • 2010.04a
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    • pp.425-428
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    • 2010
  • 멀티미디어 기기의 확산과 인터넷의 발달로 Flickr, Facebook 과 같은 사회적 네트워크를 기반으로 이미지 공유가 활발해졌다. 사회적 네트워크 사이트에서 이미지의 효율적인 검색과 관리를 위해서 태그를 이용하는 방법이 많이 사용되고 있다. 하지만 많은 양의 이미지에 수동으로 태그를 등록하는 것은 사용자에게 많은 시간과 노력을 요구한다. 태그 추천 기술은 자동으로 사용자에게 태그를 추천함으로써, 수동 태깅의 한계를 극복할 수 있는 방법이다. 본 논문에서는 사회적 네트워크를 기반으로 하는 폭소노미에서 사용자 사이의 사회적 관계를 사용자 들의 얼굴 정보를 이용하여 측정하고, 이를 활용하여 이미지 태그를 추천하는 기술을 제안한다. 제안하는 방법은 이미지의 시각 정보와 태그 분포뿐만 아니라 사용자 사이의 사회적 관계 정보를 추가로 활용한다. 실험을 통해서 제안하는 방법이 기존의 이미지 태그 추천 방법에 비해서 7% 향상된 태그 추천의 정확성을 보장하는 것을 증명하였다.

Pilot Development of Supporting Tools for Automatic Detection of Safety Standards (안전기준 자동검색을 위한 지원도구 시범개발)

  • Im, Sujung;Park, Dugkeun
    • The Journal of the Korea Contents Association
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    • v.20 no.5
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    • pp.609-622
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    • 2020
  • With the development of society, the scale of the statute is not only increasing, but also the content is getting complicated. The scale of safety standards existing in the law is also increasing and specialized, making it difficult to integrate and manage to minimize conflicts or overlaps among safety standards. For the integrated management of safety standards, a technology that searches for and extracts safety standards in laws and regulations must first be secured. In this study, considering the limitations of time and manpower, a tool for automatic detection of safety standards is developed based on several specific cases. The safety standards classified in the previous studies and the safety standards announced by the Ministry of Interior and Safety were analyzed, and also statute information which includes safety standards extracted by the National Disaster Management Institute in 2018 was collected. After the collected laws were refined and morphological analysis was performed, a safety standard thesaurus was constructed and indexed to develop a safety standard search tool. When automatic search tools are routinely applied to find safety standards in the future, it is expected that these tools will help to solve overlapping or conflicting problems of complex safety standards.

Auto-Analysis of Traffic Flow through Semantic Modeling of Moving Objects (움직임 객체의 의미적 모델링을 통한 차량 흐름 자동 분석)

  • Choi, Chang;Cho, Mi-Young;Choi, Jun-Ho;Choi, Dong-Jin;Kim, Pan-Koo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.6
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    • pp.36-45
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    • 2009
  • Recently, there are interested in the automatic traffic flowing and accident detection using various low level information from video in the road. In this paper, the automatic traffic flowing and algorithm, and application of traffic accident detection using traffic management systems are studied. To achieve these purposes, the spatio-temporal relation models using topological and directional relations have been made, then a matching of the proposed models with the directional motion verbs proposed by Levin's verbs of inherently directed motion is applied. Finally, the synonym and antonym are inserted by using WordNet. For the similarity measuring between proposed modeling and trajectory of moving object in the video, the objects are extracted, and then compared with the trajectories of moving objects by the proposed modeling. Because of the different features with each proposed modeling, the rules that have been generated will be applied to the similarity measurement by TSR (Tangent Space Representation). Through this research, we can extend our results to the automatic accident detection of vehicle using CCTV.

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Automatic generation of reliable DEM using DTED level 2 data from high resolution satellite images (고해상도 위성영상과 기존 수치표고모델을 이용하여 신뢰성이 향상된 수치표고모델의 자동 생성)

  • Lee, Tae-Yoon;Jung, Jae-Hoon;Kim, Tae-Jung
    • Spatial Information Research
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    • v.16 no.2
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    • pp.193-206
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    • 2008
  • If stereo images is used for Digital Elevation Model (DEM) generation, a DEM is generally made by matching left image against right image from stereo images. In stereo matching, tie-points are used as initial match candidate points. The number and distribution of tie-points influence the matching result. DEM made from matching result has errors such as holes, peaks, etc. These errors are usually interpolated by neighbored pixel values. In this paper, we propose the DEM generation method combined with automatic tie-points extraction using existing DEM, image pyramid, and interpolating new DEM using existing DEM for more reliable DEM. For test, we used IKONOS, QuickBird, SPOT5 stereo images and a DTED level 2 data. The test results show that the proposed method automatically makes reliable DEMs. For DEM validation, we compared heights of DEM by proposed method with height of existing DTED level 2 data. In comparison result, RMSE was under than 15 m.

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Less Informative Region Extraction for Automatically Advertisement Insertion in Sports Image (스포츠 영상 내 자동적인 광고 삽입을 위한 저정보영역 추출)

  • Jung, Jae-Young;Kim, Young-Kab
    • Journal of Digital Contents Society
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    • v.16 no.4
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    • pp.615-622
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    • 2015
  • Recently virtual advertising is located in an important area of interest in the TV market by convenience of application and reduction of cost. The methods of inserting a virtual advertising in broadcasting are Up-link that method insert the image through the production equipment of the broadcasting station and dispatch equipment and technical personnel in the shooting and Down-streaming that method insert a virtual image automatically in relay video using image processing technology. In recent years, the image processing technology is an important research area in the virtual advertising area for automatically insertion of advertising images. In this paper, we propose the method to extract less-informative region in sports video using image processing. The proposed method extracts less-Informative region through rectangle detection of Hough transform and analysis of color histogram distribution.

Efficient Content-Based Image Retrieval Method using Shape and Color feature (형태와 칼러성분을 이용한 효율적인 내용 기반의 이미지 검색 방법)

  • Youm, Sung-Ju;Kim, Woo-Saeng
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.4
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    • pp.733-744
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    • 1996
  • Content-based image retrieval(CBIR) is an image data retrieval methodology using characteristic values of image data those are generated by system automatically without any caption or text information. In this paper, we propose a content-based image data retrieval method using shape and color features of image data as characteristic values. For this, we present some image processing techniques used for feature extraction and indexing techniques based on trie and R tree for fast image data retrieval. In our approach, image query result is more reliable because both shape and color features are considered. Also, we how an image database which implemented according to our approaches and sample retrieval results which are selected by our system from 200 sample images, and an analysis about the result by considering the effect of characteristic values of shape and color.

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Automatic Extraction of Component Collaboration in Java Web Applications by Using Servlet Filters and Wrappers (자바 웹 앱에서 서블릿 필터와 래퍼를 이용한 컴포넌트 협력 과정 자동 추출 기법)

  • Oh, Jaewon;Ahn, Woo Hyun;Kim, Taegong
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.7
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    • pp.329-336
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    • 2017
  • As web apps have evolved faster and become more complex, their validation and verification have become essential for their development and maintenance. Efficient validation and verification require understanding of how web components collaborate with each other to meet user requests. Thus, this paper proposes a new approach to automatically extracting such collaboration when a user issues a request for a new page. The approach is dynamic and less sensitive to web development languages and technologies, compared to static extraction approaches. It considers an orignal web app as a black-box and does not change the app's behavior. The empirical evaluation shows that our approach can be applicable to extract component collaboration and understand the behavior of open source web apps.

Generation of Building and Contour Layers for Digital Mapping Using LiDAR Data (LiDAR 데이터를 이용한 수치지도의 건물 및 등고선 레이어 생성)

  • Lee Dong-Cheon;Yom Jae-Hong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.23 no.3
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    • pp.313-322
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    • 2005
  • Rapid advances in technology and changes in human and cultural activities bring about changes to the earth surface in terms of spatial extension as well as time frame of the changes. Such advances introduce shorter updating frequency of maps and geospatial database. To satisfy these requirements, recent research efforts in the geoinformatics field have been focused on the automation and speeding up of the mapping processes which resulted in products such as the digital photogrammetric workstation, GPSIINS, applications of satellite imagery, automatic feature extraction and the LiDAR system. The possibility of automatically extracting buildings and generating contours from airborne LiDAR data has received much attention because LiDAR data produce promising results. However, compared with the manually derived building footprints using traditional photogrammetric process, more investigation and analysis need to be carried out in terms of accuracy and efficiency. On the other hand, generation of the contours with LiDAR data is more efficient and economical in terms of the quality and accuracy. In this study, the effects of various conditions of the pre-processing phase and the subsequent building extraction and contour generation phases for digital mapping have on the accuracy were investigated.

Rule Acquisition Using Ontology Based on Graph Search (그래프 탐색을 이용한 웹으로부터의 온톨로지 기반 규칙습득)

  • Park, Sangun;Lee, Jae Kyu;Kang, Juyoung
    • Journal of Intelligence and Information Systems
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    • v.12 no.3
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    • pp.95-110
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    • 2006
  • To enhance the rule-based reasoning capability of Semantic Web, the XRML (eXtensible Rule Markup Language) approach embraces the meta-information necessary for the extraction of explicit rules from Web pages and its maintenance. To effectuate the automatic identification of rules from unstructured texts, this research develops a framework of using rule ontology. The ontology can be acquired from a similar site first, and then can be used for multiple sites in the same domain. The procedure of ontology-based rule identification is regarded as a graph search problem with incomplete nodes, and an A* algorithm is devised to solve the problem. The procedure is demonstrated with the domain of shipping rates and return policy comparison portal, which needs rule based reasoning capability to answer the customer's inquiries. An example ontology is created from Amazon.com, and is applied to the many online retailers in the same domain. The experimental result shows a high performance of this approach.

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