• Title/Summary/Keyword: Automatic Information Extraction

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Automatic Extraction of River Levee Slope Using MMS Point Cloud Data (MMS 포인트 클라우드를 활용한 하천제방 경사도 자동 추출에 관한 연구)

  • Kim, Cheolhwan;Lee, Jisang;Choi, Wonjun;Kim, Wondae;Sohn, Hong-Gyoo
    • Korean Journal of Remote Sensing
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    • v.37 no.5_3
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    • pp.1425-1434
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    • 2021
  • Continuous and periodic data acquisition must be preceded to maintain and manage the river facilities effectively. Adapting the existing general facilities methods, which include river surveying methods such as terrestrial laser scanners, total stations, and Global Navigation Satellite System (GNSS), has limitation in terms of its costs, manpower, and times to acquire spatial information since the river facilities are distributed across the wide and long area. On the other hand, the Mobile Mapping System (MMS) has comparative advantage in acquiring the data of river facilities since it constructs three-dimensional spatial information while moving. By using the MMS, 184,646,009 points could be attained for Anyang stream with a length of 4 kilometers only in 20 minutes. Levee points were divided at intervals of 10 meters so that about 378 levee cross sections were generated. In addition, the waterside maximum and average slope could be automatically calculated by separating slope plane form levee point cloud, and the accuracy of RMSE was confirmed by comparing with manually calculated slope. The reference slope was calculated manually by plotting point cloud of levee slope plane and selecting two points that use location information when calculating the slope. Also, as a result of comparing the water side slope with slope standard in basic river plan for Anyang stream, it is confirmed that inspecting the river facilities with the MMS point cloud is highly recommended than the existing river survey.

Automatic Extraction of Tree Information in Forest Areas Using Local Maxima Based on Aerial LiDAR (항공 LiDAR 기반 Local Maxima를 이용한 산림지역 수목정보 추출 자동화)

  • In-Ha Choi;Sang-Kwan Nam;Seung-Yub Kim;Dong-Gook Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1155-1164
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    • 2023
  • Currently, the National Forest Inventory (NFI) collects tree information by human, so the range and time of the survey are limited. Research is actively being conducted to extract tree information from a large area using aerial Light Detection And Ranging (LiDAR) and aerial photographs, but it does not reflect the characteristics of forest areas in Korea because it is conducted in areas with wide tree spacing or evenly spaced trees. Therefore, this study proposed a methodology for generating Digital Surface Model (DSM), Digital Elevation Model (DEM), and Canopy Height Model (CHM) images using aerial LiDAR, extracting the tree height through the local Maxima, and calculating the Diameter at Breath Height (DBH) through the DBH-tree height formula. The detection accuracy of trees extracted through the proposed methodology was 88.46%, 86.14%, and 84.31%, respectively, and the Root Mean Squared Error (RMSE) of DBH calculated based on the tree height formula was around 5cm, confirming the possibility of using the proposed methodology. It is believed that if standardized research on various types of forests is conducted in the future, the scope of automation application of the manual national forest resource survey can be expanded.

Recognition of Resident Registration Card using ART2-based RBF Network and face Verification (ART2 기반 RBF 네트워크와 얼굴 인증을 이용한 주민등록증 인식)

  • Kim Kwang-Baek;Kim Young-Ju
    • Journal of Intelligence and Information Systems
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    • v.12 no.1
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    • pp.1-15
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    • 2006
  • In Korea, a resident registration card has various personal information such as a present address, a resident registration number, a face picture and a fingerprint. A plastic-type resident card currently used is easy to forge or alter and tricks of forgery grow to be high-degree as time goes on. So, whether a resident card is forged or not is difficult to judge by only an examination with the naked eye. This paper proposed an automatic recognition method of a resident card which recognizes a resident registration number by using a refined ART2-based RBF network newly proposed and authenticates a face picture by a template image matching method. The proposed method, first, extracts areas including a resident registration number and the date of issue from a resident card image by applying Sobel masking, median filtering and horizontal smearing operations to the image in turn. To improve the extraction of individual codes from extracted areas, the original image is binarized by using a high-frequency passing filter and CDM masking is applied to the binaried image fur making image information of individual codes better. Lastly, individual codes, which are targets of recognition, are extracted by applying 4-directional contour tracking algorithm to extracted areas in the binarized image. And this paper proposed a refined ART2-based RBF network to recognize individual codes, which applies ART2 as the loaming structure of the middle layer and dynamicaly adjusts a teaming rate in the teaming of the middle and the output layers by using a fuzzy control method to improve the performance of teaming. Also, for the precise judgement of forgey of a resident card, the proposed method supports a face authentication by using a face template database and a template image matching method. For performance evaluation of the proposed method, this paper maked metamorphoses of an original image of resident card such as a forgey of face picture, an addition of noise, variations of contrast variations of intensity and image blurring, and applied these images with original images to experiments. The results of experiment showed that the proposed method is excellent in the recognition of individual codes and the face authentication fur the automatic recognition of a resident card.

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The Automatic Extraction of Hypernyms and the Development of WordNet Prototype for Korean Nouns using Korean MRD (Machine Readable Dictionary) (국어사전을 이용한 한국어 명사에 대한 상위어 자동 추출 및 WordNet의 프로토타입 개발)

  • Kim, Min-Soo;Kim, Tae-Yeon;Noh, Bong-Nam
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.6
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    • pp.847-856
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    • 1995
  • When a human recognizes nouns in a sentence, s/he associates them with the hyper concepts of onus. For computer to simulate the human's word recognition, it should build the knowledge base (WordNet)for the hyper concepts of words. Until now, works for the WordNet haven't been performed in Korea, because they need lots of human efforts and time. But, as the power of computer is radically improved and common MRD becomes available, it is more feasible to automatically construct the WordNet. This paper proposes the method that automatically builds the WordNet of Korean nouns by using the descripti on of onus in Korean MRD, and it proposes the rules for extracting the hyper concepts (hypernyms)by analyzing structrual characteristics of Korean. The rules effect such characteristics as a headword lies on the rear part of sentences and the descriptive sentences of nouns have special structure. In addition, the WordNet prototype of Korean Nouns is developed, which is made by combining the hypernyms produced by the rules mentioned above. It extracts the hypernyms of about 2,500 sample words, and the result shows that about 92per cents of hypernyms are correct.

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Application of the Developed Pre- and Post-Processing System to Yongdamdam Watershed using PRMS Hydrological Model (수문학적 유역특성자료 자동화 추출 및 분석시스템 적용 (II) -PRMS 모형을 이용한 용담댐 유역을 대상으로-)

  • Kwon, Hyung-Joong;Hwang, Eui-Ho;Lee, Geun-Sang;Yu, Byeong-Hyeok;Koh, Deuk-Koo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.11 no.3
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    • pp.13-22
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    • 2008
  • The objective of this study is to evaluate the applicability of extracted PRMS input parameters by KGIS-Hydrology over Yongdam-Dam watershed. KGIS-Hydrology is a system for automatic extraction and analysis of watershed characteristic data. Input parameters of PRMS were generated from GIS data (DEM, soil, forest type, etc.) using KGIS-Hydrology. Multi-temporal meteorological data from Jangsu station of KMA (Korea Meteorological Administration) were used for all simulation periods. Input parameters of PRMS were optimized using observed runoff data of Yongdam-Dam station (1966-2001) and validated using observed runoff data of Yongdam-Dam station (2002-2006, Yongdam-Dam watershed). The results showed that the simulated flows were much closed to the observed flows of Yongdam-Dam (2002-2006) and Donghyang (2001-2004) station by 0.49~0.83 and 0.57~0.75 model efficiencies, respectively.

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Dynamic ontology construction algorithm from Wikipedia and its application toward real-time nation image analysis (국가이미지 분석을 위한 위키피디아 실시간 동적 온톨로지 구축 알고리즘 및 적용)

  • Lee, Youngwhan
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.4
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    • pp.979-991
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    • 2016
  • Measuring nation images was a challenging task when employing offline surveys was the only option. It was not only prohibitively expensive, but too much time-consuming and therefore unfitted to this rapidly changing world. Although demands for monitoring real-time nation images were ever-increasing, an affordable and reliable solution to measure nation images has not been available up to this date. The researcher in this study developed a semi-automatic ontology construction algorithm, named "double-crossing double keyword collection (or DCDKC)" to measure nation images from Wikipedia in real-time. The ontology, WikiOnto, can be used to reflect dynamic image changes. In this study, an instance of WikiOnto was constructed by applying the algorithm to the big-three exporting countries in East Asia, Korea, Japan, and China. Then, the numbers of page views for words in the instance of WikiOnto were counted. A collection of the counting for each country was compared to each other to inspect the possibility to use for dynamic nation images. As for the conclusion, the result shows how the images of the three countries have changed for the period the study was performed. It confirms that DCDKC can very well be used for a real-time nation-image monitoring system.

Indexing and Retrieval Mechanism using Variation Patterns of Theme Melodies in Content-based Music Information Retrievals (내용 기반 음악 정보 검색에서 주제 선율의 변화 패턴을 이용한 색인 및 검색 기법)

  • 구경이;신창환;김유성
    • Journal of KIISE:Databases
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    • v.30 no.5
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    • pp.507-520
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    • 2003
  • In this paper, an automatic construction method of theme melody index for large music database and an associative content-based music retrieval mechanism in which the constructed theme melody index is mainly used to improve the users' response time are proposed. First, the system automatically extracted the theme melody from a music file by the graphical clustering algorithm based on the similarities between motifs of the music. To place an extracted theme melody into the metric space of M-tree, we chose the average length variation and the average pitch variation of the theme melody as the major features. Moreover, we added the pitch signature and length signature which summarize the pitch variation pattern and the length variation pattern of a theme melody, respectively, to increase the precision of retrieval results. We also proposed the associative content-based music retrieval mechanism in which the k-nearest neighborhood searching and the range searching algorithms of M-tree are used to select the similar melodies to user's query melody from the theme melody index. To improve the users' satisfaction, the proposed retrieval mechanism includes ranking and user's relevance feedback functions. Also, we implemented the proposed mechanisms as the essential components of content-based music retrieval systems to verify the usefulness.

Multiple Cause Model-based Topic Extraction and Semantic Kernel Construction from Text Documents (다중요인모델에 기반한 텍스트 문서에서의 토픽 추출 및 의미 커널 구축)

  • 장정호;장병탁
    • Journal of KIISE:Software and Applications
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    • v.31 no.5
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    • pp.595-604
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    • 2004
  • Automatic analysis of concepts or semantic relations from text documents enables not only an efficient acquisition of relevant information, but also a comparison of documents in the concept level. We present a multiple cause model-based approach to text analysis, where latent topics are automatically extracted from document sets and similarity between documents is measured by semantic kernels constructed from the extracted topics. In our approach, a document is assumed to be generated by various combinations of underlying topics. A topic is defined by a set of words that are related to the same topic or cooccur frequently within a document. In a network representing a multiple-cause model, each topic is identified by a group of words having high connection weights from a latent node. In order to facilitate teaming and inferences in multiple-cause models, some approximation methods are required and we utilize an approximation by Helmholtz machines. In an experiment on TDT-2 data set, we extract sets of meaningful words where each set contains some theme-specific terms. Using semantic kernels constructed from latent topics extracted by multiple cause models, we also achieve significant improvements over the basic vector space model in terms of retrieval effectiveness.

Automatic Text Extraction from News Video using Morphology and Text Shape (형태학과 문자의 모양을 이용한 뉴스 비디오에서의 자동 문자 추출)

  • Jang, In-Young;Ko, Byoung-Chul;Kim, Kil-Cheon;Byun, Hye-Ran
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.4
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    • pp.479-488
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    • 2002
  • In recent years the amount of digital video used has risen dramatically to keep pace with the increasing use of the Internet and consequently an automated method is needed for indexing digital video databases. Textual information, both superimposed and embedded scene texts, appearing in a digital video can be a crucial clue for helping the video indexing. In this paper, a new method is presented to extract both superimposed and embedded scene texts in a freeze-frame of news video. The algorithm is summarized in the following three steps. For the first step, a color image is converted into a gray-level image and applies contrast stretching to enhance the contrast of the input image. Then, a modified local adaptive thresholding is applied to the contrast-stretched image. The second step is divided into three processes: eliminating text-like components by applying erosion, dilation, and (OpenClose+CloseOpen)/2 morphological operations, maintaining text components using (OpenClose+CloseOpen)/2 operation with a new Geo-correction method, and subtracting two result images for eliminating false-positive components further. In the third filtering step, the characteristics of each component such as the ratio of the number of pixels in each candidate component to the number of its boundary pixels and the ratio of the minor to the major axis of each bounding box are used. Acceptable results have been obtained using the proposed method on 300 news images with a recognition rate of 93.6%. Also, my method indicates a good performance on all the various kinds of images by adjusting the size of the structuring element.

Synthesis of Realistic Facial Expression using a Nonlinear Model for Skin Color Change (비선형 피부색 변화 모델을 이용한 실감적인 표정 합성)

  • Lee Jeong-Ho;Park Hyun;Moon Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.43 no.3 s.309
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    • pp.67-75
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    • 2006
  • Facial expressions exhibit not only facial feature motions, but also subtle changes in illumination and appearance. Since it is difficult to generate realistic facial expressions by using only geometric deformations, detailed features such as textures should also be deformed to achieve more realistic expression. The existing methods such as the expression ratio image have drawbacks, in that detailed changes of complexion by lighting can not be generated properly. In this paper, we propose a nonlinear model for skin color change and a model-based synthesis method for facial expression that can apply realistic expression details under different lighting conditions. The proposed method is composed of the following three steps; automatic extraction of facial features using active appearance model and geometric deformation of expression using warping, generation of facial expression using a model for nonlinear skin color change, and synthesis of original face with generated expression using a blending ratio that is computed by the Euclidean distance transform. Experimental results show that the proposed method generate realistic facial expressions under various lighting conditions.