• Title/Summary/Keyword: 자동정보 추출

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Detection of Text Candidate Regions using Region Information-based Genetic Algorithm (영역정보기반의 유전자알고리즘을 이용한 텍스트 후보영역 검출)

  • Oh, Jun-Taek;Kim, Wook-Hyun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.6
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    • pp.70-77
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    • 2008
  • This paper proposes a new text candidate region detection method that uses genetic algorithm based on information of the segmented regions. In image segmentation, a classification of the pixels at each color channel and a reclassification of the region-unit for reducing inhomogeneous clusters are performed. EWFCM(Entropy-based Weighted C-Means) algorithm to classify the pixels at each color channel is an improved FCM algorithm added with spatial information, and therefore it removes the meaningless regions like noise. A region-based reclassification based on a similarity between each segmented region of the most inhomogeneous cluster and the other clusters reduces the inhomogeneous clusters more efficiently than pixel- and cluster-based reclassifications. And detecting text candidate regions is performed by genetic algorithm based on energy and variance of the directional edge components, the number, and a size of the segmented regions. The region information-based detection method can singles out semantic text candidate regions more accurately than pixel-based detection method and the detection results will be more useful in recognizing the text regions hereafter. Experiments showed the results of the segmentation and the detection. And it confirmed that the proposed method was superior to the existing methods.

Extracting Beginning Boundaries for Efficient Management of Movie Storytelling Contents (스토리텔링 콘텐츠의 효과적인 관리를 위한 영화 스토리 발단부의 자동 경계 추출)

  • Park, Seung-Bo;You, Eun-Soon;Jung, Jason J.
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.279-292
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    • 2011
  • Movie is a representative media that can transmit stories to audiences. Basically, a story is described by characters in the movie. Different from other simple videos, movies deploy narrative structures for explaining various conflicts or collaborations between characters. These narrative structures consist of 3 main acts, which are beginning, middle, and ending. The beginning act includes 1) introduction to main characters and backgrounds, and 2) conflicts implication and clues for incidents. The middle act describes the events developed by both inside and outside factors and the story dramatic tension heighten. Finally, in the end act, the events are developed are resolved, and the topic of story and message of writer are transmitted. When story information is extracted from movie, it is needed to consider that it has different weights by narrative structure. Namely, when some information is extracted, it has a different influence to story deployment depending on where it locates at the beginning, middle and end acts. The beginning act is the part that exposes to audiences for story set-up various information such as setting of characters and depiction of backgrounds. And thus, it is necessary to extract much kind information from the beginning act in order to abstract a movie or retrieve character information. Thereby, this paper proposes a novel method for extracting the beginning boundaries. It is the method that detects a boundary scene between the beginning act and middle using the accumulation graph of characters. The beginning act consists of the scenes that introduce important characters, imply the conflict relationship between them, and suggest clues to resolve troubles. First, a scene that the new important characters don't appear any more should be detected in order to extract a scene completed the introduction of them. The important characters mean the major and minor characters, which can be dealt as important characters since they lead story progression. Extra should be excluded in order to extract a scene completed the introduction of important characters in the accumulation graph of characters. Extra means the characters that appear only several scenes. Second, the inflection point is detected in the accumulation graph of characters. It is the point that the increasing line changes to horizontal line. Namely, when the slope of line keeps zero during long scenes, starting point of this line with zero slope becomes the inflection point. Inflection point will be detected in the accumulation graph of characters without extra. Third, several scenes are considered as additional story progression such as conflicts implication and clues suggestion. Actually, movie story can arrive at a scene located between beginning act and middle when additional several scenes are elapsed after the introduction of important characters. We will decide the ratio of additional scenes for total scenes by experiment in order to detect this scene. The ratio of additional scenes is gained as 7.67% by experiment. It is the story inflection point to change from beginning to middle act when this ratio is added to the inflection point of graph. Our proposed method consists of these three steps. We selected 10 movies for experiment and evaluation. These movies consisted of various genres. By measuring the accuracy of boundary detection experiment, we have shown that the proposed method is more efficient.

Spam-Mail Filtering System Using Weighted Bayesian Classifier (가중치가 부여된 베이지안 분류자를 이용한 스팸 메일 필터링 시스템)

  • 김현준;정재은;조근식
    • Journal of KIISE:Software and Applications
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    • v.31 no.8
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    • pp.1092-1100
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    • 2004
  • An E-mails have regarded as one of the most popular methods for exchanging information because of easy usage and low cost. Meanwhile, exponentially growing unwanted mails in user's mailbox have been raised as main problem. Recognizing this issue, Korean government established a law in order to prevent e-mail abuse. In this paper we suggest hybrid spam mail filtering system using weighted Bayesian classifier which is extended from naive Bayesian classifier by adding the concept of preprocessing and intelligent agents. This system can classify spam mails automatically by using training data without manual definition of message rules. Particularly, we improved filtering efficiency by imposing weight on some character by feature extraction from spam mails. Finally, we show efficiency comparison among four cases - naive Bayesian, weighting on e-mail header, weighting on HTML tags, weighting on hyperlinks and combining all of four cases. As compared with naive Bayesian classifier, the proposed system obtained 5.7% decreased precision, while the recall and F-measure of this system increased by 33.3% and 31.2%, respectively.

An Efficient Location Based Service based on Mobile Augmented Reality applying Street Data extracted from Digital Map (도로 데이터를 활용한 모바일 증강현실 기반의 효율적인 위치기반 서비스)

  • Lee, Jeong Hwan;Jang, Yong Hee;Kwon, Yong Jin
    • Spatial Information Research
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    • v.21 no.4
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    • pp.63-70
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    • 2013
  • With the increasing use of high-performance mobile devices such as smartphones, users have been able to connect to the Internet anywhere, anytime, so that Location Based Services(LBSes) have been popular among the users in order to obtain personalized information associated with their locations. The services have advanced to provide the information realistically and intuitively by adopting Augmented Reality(AR) technology, where the technology utilizes various sensors embedded in the mobile devices. However, the services have inherent problems due to the small screen size of the mobile devices and the complexity of the real world environment. Overlapping contents on a small screen and user's possible movement should be taken into consideration in displaying the icons on objects that block user's environment such as trees and buildings. The problems mainly happen when the services use only user's location and sensor data to calculate the position of the displayed information. In order to solve the problems, this paper proposes a method that applies street data extracted from a digital map. The method uses the street data as well as the location and direction data to determine contents that are placed on both sides of a virtual street which augments the real street. With scrolling the virtual street, which means a virtual movement, some information far away from the location of the user can be identified without user's actual movement. Also the proposed method is implemented for region "Aenigol", and the efficiency and usefulness of the method is verified.

Development of Portable Multi-function Sensor (Mini CPT Cone + VWC Sensor) to Improve the Efficiency of Slope Inspection (비탈면 점검 효율화를 위한 휴대형 복합센서 개발)

  • Kim, Jong-Woo;Jho, Youn-Beom
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.1
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    • pp.49-57
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    • 2022
  • In order to efficiently analysis the stability of a slope, measuring the shear strength of soil is needed. The Standard Penetration Test (SPT) is not appropriate for a slope inspection due to cost and weights. One of the ways to effectively measure the N-value is the Dynamic Cone Penetration Test (DCPT). This study was performed to develop a minimized multi-function sensors that can easily estimate CPT values and Volumetric Water Content. N value with multi-fuction sensor DCPT showed -2.5 ~ +3.9% error compared with the SPT N value (reference value) in the field tests. Also, the developed multi-fuction sensor system was tested the correlation between the CPT test and the portable tester with indoor test. The test result showed 0.85 R2 value in soil, 0.83 in weathered soil, and 0.98 in mixed soil. As a result of the field test, the multi-function sensor shows the excellent field applicability of the proposed sensor system. After further research, it is expected that the portable multi-function sensor will be useful for general slope inspection.

Development of the Algofithm for Gaussian Mixture Models based Traffic Accident Auto-Detection in Freeway (GMM(Gaussian Mixture Model)을 적용한 영상처리기법의 연속류도로 사고 자동검지 알고리즘 개발)

  • O, Ju-Taek;Im, Jae-Geuk;Yeo, Tae-Dong
    • Journal of Korean Society of Transportation
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    • v.28 no.3
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    • pp.169-183
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    • 2010
  • Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a freeway and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, existing technologies, this freeway attribute, velocity changes, volume changes, occupancy changes reflect judge the primary. Furthermore, We pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian Mixture model analytical method which has been considered the best among well-known environmental obstacle reduction methods. Therefore, in this way, the accident was the final decision. Also, environmental factors occur frequently, and with the index finger situations, effectively reducing that can actively and environmentally adaptive techniques through accident final judgment. This implementation of the evaluate performance of the experiment road of 12 incidents in simulated and the jang-hang IC's real-time accident experiment. As a result, the do well detection 93.33%, false alarm 6.7% as showed high reliability.

A Practical Feature Extraction for Improving Accuracy and Speed of IDS Alerts Classification Models Based on Machine Learning (기계학습 기반 IDS 보안이벤트 분류 모델의 정확도 및 신속도 향상을 위한 실용적 feature 추출 연구)

  • Shin, Iksoo;Song, Jungsuk;Choi, Jangwon;Kwon, Taewoong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.2
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    • pp.385-395
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    • 2018
  • With the development of Internet, cyber attack has become a major threat. To detect cyber attacks, intrusion detection system(IDS) has been widely deployed. But IDS has a critical weakness which is that it generates a large number of false alarms. One of the promising techniques that reduce the false alarms in real time is machine learning. However, there are problems that must be solved to use machine learning. So, many machine learning approaches have been applied to this field. But so far, researchers have not focused on features. Despite the features of IDS alerts are important for performance of model, the approach to feature is ignored. In this paper, we propose new feature set which can improve the performance of model and can be extracted from a single alarm. New features are motivated from security analyst's know-how. We trained and tested the proposed model applied new feature set with real IDS alerts. Experimental results indicate the proposed model can achieve better accuracy and false positive rate than SVM model with ordinary features.

Adaptive Image Content-Based Retrieval Techniques for Multiple Queries (다중 질의를 위한 적응적 영상 내용 기반 검색 기법)

  • Hong Jong-Sun;Kang Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.73-80
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    • 2005
  • Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

LiDAR Ground Classification Enhancement Based on Weighted Gradient Kernel (가중 경사 커널 기반 LiDAR 미추출 지형 분류 개선)

  • Lee, Ho-Young;An, Seung-Man;Kim, Sung-Su;Sung, Hyo-Hyun;Kim, Chang-Hun
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.2
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    • pp.29-33
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    • 2010
  • The purpose of LiDAR ground classification is to archive both goals which are acquiring confident ground points with high precision and describing ground shape in detail. In spite of many studies about developing optimized algorithms to kick out this, it is very difficult to classify ground points and describing ground shape by airborne LiDAR data. Especially it is more difficult in a dense forested area like Korea. Principle misclassification was mainly caused by complex forest canopy hierarchy in Korea and relatively coarse LiDAR points density for ground classification. Unfortunately, a lot of LiDAR surveying performed in summer in South Korea. And by that reason, schematic LiDAR points distribution is very different from those of Europe. So, this study propose enhanced ground classification method considering Korean land cover characteristics. Firstly, this study designate highly confident candidated LiDAR points as a first ground points which is acquired by using big roller classification algorithm. Secondly, this study applied weighted gradient kernel(WGK) algorithm to find and include highly expected ground points from the remained candidate points. This study methods is very useful for reconstruct deformed terrain due to misclassification results by detecting and include important terrain model key points for describing ground shape at site. Especially in the case of deformed bank side of river area, this study showed highly enhanced classification and reconstruction results by using WGK algorithm.

Development of Damage Evaluation Technology Considering Variability for Cable Damage Detection of Cable-Stayed Bridges (사장교의 케이블 손상 검출을 위한 변동성이 고려된 손상평가 기술 개발)

  • Ko, Byeong-Chan;Heo, Gwang-Hee;Park, Chae-Rin;Seo, Young-Deuk;Kim, Chung-Gil
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.24 no.6
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    • pp.77-84
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    • 2020
  • In this paper, we developed a damage evaluation technique that can determine the damage location of a long-sized structure such as a cable-stayed bridge, and verified the performance of the developed technique through experiments. The damage assessment method aims to extract data that can evaluate the damage of the structure without the undamage data and can determine the damage location only by analyzing the response data of the structure. To complete this goal, we developed a damage assessment technique that considers variability based on the IMD theory, which is a statistical pattern recognition technique, to identify the damage location. To complete this goal, we developed a damage assessment technique that considers variability based on the IMD theory, which is a statistical pattern recognition technique, to identify the damage location. To evaluate the performance of the developed technique experimentally, cable damage experiments were conducted on model cable-stayed bridges. As a result, the damage assessment method considering variability automatically outputs the damageless data according to external force, and it is confirmed that the performance of extracting information that can determine the damage location of the cable through the analysis of the outputted damageless data and the measured damage data is shown.