• Title/Summary/Keyword: 자동정보 추출

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Design and Implementation of an Open Object Management System for Spatial Data Mining (공간 데이타 마이닝을 위한 개방형 객체 관리 시스템의 설계 및 구현)

  • Yun, Jae-Kwan;Oh, Byoung-Woo;Han, Ki-Joon
    • Journal of Korea Spatial Information System Society
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    • v.1 no.1 s.1
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    • pp.5-18
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    • 1999
  • Recently, the necessity of automatic knowledge extraction from spatial data stored in spatial databases has been increased. Spatial data mining can be defined as the extraction of implicit knowledge, spatial relationships, or other knowledge not explicitly stored in spatial databases. In order to extract useful knowledge from spatial data, an object management system that can store spatial data efficiently, provide very fast indexing & searching mechanisms, and support a distributed computing environment is needed. In this paper, we designed and implemented an open object management system for spatial data mining, that supports efficient management of spatial, aspatial, and knowledge data. In order to develop this system, we used Open OODB that is a widely used object management system. However, the lark of facilities for spatial data mining in Open OODB, we extended it to support spatial data type, dynamic class generation, object-oriented inheritance, spatial index, spatial operations, etc. In addition, for further increasement of interoperability with other spatial database management systems or data mining systems, we adopted international standards such as ODMG 2.0 for data modeling, SDTS(Spatial Data Transfer Standard) for modeling and exchanging spatial data, and OpenGIS Simple Features Specification for CORBA for connecting clients and servers efficiently.

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Change Detection Using Spectral Unmixing and IEA(Iterative Error Analysis) for Hyperspectral Images (IEA(Iterative Error Analysis)와 분광혼합분석기법을 이용한 초분광영상의 변화탐지)

  • Song, Ahram;Choi, Jaewan;Chang, Anjin;Kim, Yongil
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.361-370
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    • 2015
  • Various algorithms such as Chronochrome(CC), Principle Component Analysis(PCA), and spectral unmixing have been studied for hyperspectral change detection. Change detection by spectral unmixing offers useful information on the nature of the change compared to the other change detection methods which provide only the locations of changes in the scene. However, hyperspectral change detection by spectral unmixing is still in an early stage. This research proposed a new approach to extract endmembers, which have identical properties in temporally different images, by Iterative Error Analysis (IEA) and Spectral Angle Mapper(SAM). The change map obtained from the difference of abundance efficiently showed the changed pixels. Simulated images generated from Compact Airborne Spectrographic Imager (CASI) and Hyperion were used for change detection, and the experimental results showed that the proposed method performed better than CC, PCA, and spectral unmixing using N-FINDR. The proposed method has the advantage of automatically extracting endmembers without prior information, and it could be applicable for the real images composed of many materials.

Object/Non-object Image Classification Based on the Detection of Objects of Interest (관심 객체 검출에 기반한 객체 및 비객체 영상 분류 기법)

  • Kim Sung-Young
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.2 s.40
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    • pp.25-33
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    • 2006
  • We propose a method that automatically classifies the images into the object and non-object images. An object image is the image with object(s). An object in an image is defined as a set of regions that lie around center of the image and have significant color distribution against the other surround (or background) regions. We define four measures based on the characteristics of an object to classify the images. The center significance is calculated from the difference in color distribution between the center area and its surrounding region. Second measure is the variance of significantly correlated colors in the image plane. Significantly correlated colors are first defined as the colors of two adjacent pixels that appear more frequently around center of an image rather than at the background of the image. Third one is edge strength at the boundary of candidate for the object. By the way, it is computationally expensive to extract third value because central objects are extracted. So, we define fourth measure which is similar with third measure in characteristic. Fourth one can be calculated more fast but show less accuracy than third one. To classify the images we combine each measure by training the neural network and SYM. We compare classification accuracies of these two classifiers.

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A New Locomotor Evaluation System for Mouses Based on Continuous Shooting Images (연속 촬영 이미지를 이용한 Mouse의 운동 능력 평가 시스템)

  • Kwak, Ho-Young;Huh, Jisoon;Lee, Won Joo
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.1
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    • pp.153-161
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    • 2015
  • In this paper, we propose a locomotor evaluation System for mouse based on continuous shooting images. In the field of veterinary medicine and animal studies are subjected to using the mouse for the quality of human life. In particular, during the experiments using the artificially created mice injury, through a variety of scoring and a lot of experiments to measure the extent of recovery from the injury. The traditional method of measuring the quantity of exercise while in this experiment was made of a method for directly observing person. The proposed system performs the continuous shooting per unit of time specified by the movement of the mouse is extracted from a continuous image shooting with the outline of a mouse point cloud. And using the extracted point cloud to extract again the inner contour of the body of the mouse. So using the new point cloud obtained its center, Then, using the center point calculated by accumulating the distance between two points on locomotor evaluation system design and implement to obtain the total distance the mouse moves over a unit of time.

Reproducing Summarized Video Contents based on Camera Framing and Focus

  • Hyung Lee;E-Jung Choi
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.85-92
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    • 2023
  • In this paper, we propose a method for automatically generating story-based abbreviated summaries from long-form dramas and movies. From the shooting stage, the basic premise was to compose a frame with illusion of depth considering the golden division as well as focus on the object of interest to focus the viewer's attention in terms of content delivery. To consider how to extract the appropriate frames for this purpose, we utilized elemental techniques that have been utilized in previous work on scene and shot detection, as well as work on identifying focus-related blur. After converting the videos shared on YouTube to frame-by-frame, we divided them into a entire frame and three partial regions for feature extraction, and calculated the results of applying Laplacian operator and FFT to each region to choose the FFT with relative consistency and robustness. By comparing the calculated values for the entire frame with the calculated values for the three regions, the target frames were selected based on the condition that relatively sharp regions could be identified. Based on the selected results, the final frames were extracted by combining the results of an offline change point detection method to ensure the continuity of the frames within the shot, and an edit decision list was constructed to produce an abbreviated summary of 62.77% of the footage with F1-Score of 75.9%

Decision of the Korean Speech Act using Feature Selection Method (자질 선택 기법을 이용한 한국어 화행 결정)

  • 김경선;서정연
    • Journal of KIISE:Software and Applications
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    • v.30 no.3_4
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    • pp.278-284
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    • 2003
  • Speech act is the speaker's intentions indicated through utterances. It is important for understanding natural language dialogues and generating responses. This paper proposes the method of two stage that increases the performance of the korean speech act decision. The first stage is to select features from the part of speech results in sentence and from the context that uses previous speech acts. We use x$^2$ statistics(CHI) for selecting features that have showed high performance in text categorization. The second stage is to determine speech act with selected features and Neural Network. The proposed method shows the possibility of automatic speech act decision using only POS results, makes good performance by using the higher informative features and speed up by decreasing the number of features. We tested the system using our proposed method in Korean dialogue corpus transcribed from recording in real fields, and this corpus consists of 10,285 utterances and 17 speech acts. We trained it with 8,349 utterances and have test it with 1,936 utterances, obtained the correct speech act for 1,709 utterances(88.3%). This result is about 8% higher accuracy than without selecting features.

Validation of Ship Detection by the RADARSAT Synthetic Aperture Radar and KOMPSAT EOC: Field Experiments (RADARSAT SAR와 KOMPSAT EOC에 의한 선박 탐지의 검증: 현장 실험)

  • Yang Chan-Su;Kim Sun-Young
    • Proceedings of KOSOMES biannual meeting
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    • 2004.11a
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    • pp.43-47
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    • 2004
  • Two different sensors (here, KOMPSAT and RADARSAT) are considered for ship detection, and are used to delineate the detection performance for their data The experiments are set for coastal regions of Mokpo Port and Ulsan Port and field experiments on board pilot boat are conducted to collect in situ ship validation information such as ship type and length This paper introduce mainly the experiment result of ship detection by both RADARSAT SAR imagery and land-based RADAR data, operated by the local Authority of South Korean, so called vessel traffic system (VTS) radar. Fine imagery of Ulsan Port was acquired on June 19, 2004 and in-situ data such as wind speed and direction, taking pictures of ships and natural features were obtained aboard a pilot ship. North winds, with a maximum speed of 3.1 m/s were recorded Ship's position, size and shape and natural features of breakwaters, oil pipeline and alongside ship were compared using SAR and VTS. It is shown that KOMPSAT/EOC has a good performance in the detection of a moving ship at a speed of kts or more an hour that ship and its wake can be imaged. The detection capability of RADARSAT doesn't matter how fast ship is running and depends on a ship itself, e.g. its material, length and type. Our results indicate that SAR can be applicable to automated ship detection for a VTS and SAR combination service.

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A Hybrid Approach of Efficient Facial Feature Detection and Tracking for Real-time Face Direction Estimation (실시간 얼굴 방향성 추정을 위한 효율적인 얼굴 특성 검출과 추적의 결합방법)

  • Kim, Woonggi;Chun, Junchul
    • Journal of Internet Computing and Services
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    • v.14 no.6
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    • pp.117-124
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    • 2013
  • In this paper, we present a new method which efficiently estimates a face direction from a sequences of input video images in real time fashion. For this work, the proposed method performs detecting the facial region and major facial features such as both eyes, nose and mouth by using the Haar-like feature, which is relatively not sensitive against light variation, from the detected facial area. Then, it becomes able to track the feature points from every frame using optical flow in real time fashion, and determine the direction of the face based on the feature points tracked. Further, in order to prevent the erroneously recognizing the false positions of the facial features when if the coordinates of the features are lost during the tracking by using optical flow, the proposed method determines the validity of locations of the facial features using the template matching of detected facial features in real time. Depending on the correlation rate of re-considering the detection of the features by the template matching, the face direction estimation process is divided into detecting the facial features again or tracking features while determining the direction of the face. The template matching initially saves the location information of 4 facial features such as the left and right eye, the end of nose and mouse in facial feature detection phase and reevaluated these information when the similarity measure between the stored information and the traced facial information by optical flow is exceed a certain level of threshold by detecting the new facial features from the input image. The proposed approach automatically combines the phase of detecting facial features and the phase of tracking features reciprocally and enables to estimate face pose stably in a real-time fashion. From the experiment, we can prove that the proposed method efficiently estimates face direction.

Analysis System of Endoscopic Image of Early Gastric Cancer (조기 위암의 내시경 영상 분석 시스템)

  • Kim, Kwang-Baek;Lim, Eun-Kyung;Kim, Gwang-Ha
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.4
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    • pp.473-478
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    • 2005
  • The gastric cancer takes the great part of the cancer occurrence and the mortality from cancer in Korea, and the early detection of gastric cancer is very important in the treatment and convalescence. This paper. for the early detection of gastric cancer, Proposes the analysis system of endoscopic image of the stomach that detects the abnormal region by using the change of color in the image and provides the surface tissue information to the detector. While the advanced inflammation and the cancer may be easily detected, the early inflammation and the cancer have a difficulty in detection and require the more attention lot detection. This paper, at first, converts the endoscopic image to the Image of IHb(Index of Hemoglobin) model and removes noises incurred by illumination, and next, automatically detects the regions suspected as cancer and provides the related information to the detector, or provides the surface tissue information for the regions appointed by the detector. This paper does not intend to provide the final diagnosis of the detected abnormal regions as gastric cancer, but provides the supplementary mean that reduces the load and mistaken diagnosis of the detector by automatically detecting the abnormal regions being not easily detected by human eyes and providing the additional information for the diagnosis. The experiments using practical endoscopic images for performance evaluation showed that the proposed system is effective in the analysis of endoscopic image of the stomach.

Automatic Segmentation of Trabecular Bone Based on Sphere Fitting for Micro-CT Bone Analysis (마이크로-CT 뼈 영상 분석을 위한 구 정합 기반 해면뼈의 자동 분할)

  • Kang, Sun Kyung;Kim, Young Un;Jung, Sung Tae
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.8
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    • pp.329-334
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    • 2014
  • In this study, a new method that automatically segments trabecular bone for its morphological analysis using micro-computed tomography imaging was proposed. In the proposed method, the bone region was extracted using a threshold value, and the outer boundary of the bone was detected. The sphere of maximum size with the corresponding voxel as the center was obtained by applying the sphere-fitting method to each voxel of the bone region. If this sphere includes the outer boundary of the bone, the voxels included in the sphere are classified as cortical bone; otherwise, they are classified as trabecular bone. The proposed method was applied to images of the distal femurs of 15 mice, and comparative experiments, with results manually divided by a person, were performed. Four morphological parameters-BV/TV, Tb.Th, Tb.Sp, and Tb.N-for the segmented trabecular bone were measured. The results were compared by regression analysis and the Bland-Altman method; BV/TV, Tb.Th, Tb.Sp, and Tb.N were all in the credible range. In addition, not only can the sphere-fitting method be simply implemented, but trabecular bone can also be divided precisely by using the three-dimensional information.