• Title/Summary/Keyword: Image pattern analysis

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Door Traversing for A Mobile Robot in Complex Environment (복잡한 환경에서 자율이동 로봇의 문 통과방법)

  • Kim Young-Joong;Lim Myo-Teak;Seo Min-Wook
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.7
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    • pp.447-452
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    • 2005
  • This paper presents a method that a mobile robot finds location of doors in complex environments and safely traverses the door PCA(Principal Component Analysis) algorithm using the vision information is used for a robot to find the location of door, PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding pattern in data of high dimension. Fuzzy controller using a sonar data is used for a robot to avoid obstacles and traverse the doors.

Automated System on Extracting Digital Pattern for TDGS Image Analysis (TDGS 영상 분석을 통한 자동적 디지털 패턴의 추출)

  • Chang, Hwan;Park, You-Na;Lee, Bog-Ju
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.05a
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    • pp.707-710
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    • 2003
  • 본 논문은 2차원 전기영동에 의해 나타나는 TOGS 영상을 분석하기 위한 시스템으로 실험적인 특성상 젤 위에 나타나는 반점들의 불규칙한 요소들이 많고 영상의 상태가 좋지 않은 경우 명암도가 떨어지는 반점들의 구분이 힘들게 된다. 기존의 전문가의 육안에 의한 TDGS 영상 분석은 그러한 불안적 요소들에 대해 유연하게 대처할 수 있는 능력이 있었다. 하지만, 그러한 예외적인 경우를 컴퓨터가 처리하기 위해서는 영상의 지역적 상태에 맞는 융통성 있는 영상처리 과정이 필요하고, 실제 분석에 사용되지 않는 반정들을 제외한 유효한 디지털 패턴의 판별이 요구된다. 이에 본 논문에서는 영상의 지역적 특성을 효과적으로 반영한 동적 이진화 방법을 통해 후보 패턴들을 추출하고, 모든 샘플들의 기준이 되는 Reference 패턴과 후보 패턴의 point matching 과정을 통해 디지털 패턴을 추출한다.

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Bender Gestalt Test Image Recognition with Convolutional Neural Network (합성곱 신경망을 이용한 Bender Gestalt Test 영상인식)

  • Chang, Won-Du;Yang, Young-Jun;Choi, Seong-Jin
    • Journal of Korea Multimedia Society
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    • v.22 no.4
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    • pp.455-462
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    • 2019
  • This paper proposes a method of utilizing convolutional neural network to classify the images of Bender Gestalt Test (BGT), which is a tool to understand and analyze a person's characteristic. The proposed network is composed of 29 layers including 18 convolutional layers and 2 fully connected layers, where the network is to be trained with augmented images. To verify the proposed method, 10 fold validation was adopted. In results, the proposed method classified the images into 9 classes with the mean f1 score of 97.05%, which is 13.71%p higher than a previous method. The analysis of the results shows the classification accuracy of the proposed method is stable over all the patterns as the worst f1 score among all the patterns was 92.11%.

On-line Data Analysis for Marketing Service including Golf Image Contents (골프공 영상콘텐츠를 포함한 마케팅서비스를 위한 온라인 자료분석에 관한 연구)

  • Lee, Hyun-chang;Jin, Chan-Yong;Shin, Seong-yoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.379-381
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    • 2016
  • Among the various sports, recognition of golf sport is changing the privileged classes sport into a popular sport. In this kind of sport area, there are many loyal customers of golf sport relatively compared to the other marketing products or sports. Therefore, in this paper, we have analyzed the online buying pattern of customers through the popularization of golf such as golf ball or accessories and want to promote activation marketing in the online environment. For these, we suggest the way to promote marketing activation by analyzing online data.

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Video Road Vehicle Detection and Tracking based on OpenCV

  • Hou, Wei;Wu, Zhenzhen;Jung, Hoekyung
    • Journal of information and communication convergence engineering
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    • v.20 no.3
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    • pp.226-233
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    • 2022
  • Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.

Real-Time Human Tracker Based on Location and Motion Recognition of User for Smart Home (스마트 홈을 위한 사용자 위치와 모션 인식 기반의 실시간 휴먼 트랙커)

  • Choi, Jong-Hwa;Park, Se-Young;Shin, Dong-Kyoo;Shin, Dong-Il
    • The KIPS Transactions:PartA
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    • v.16A no.3
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    • pp.209-216
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    • 2009
  • The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

Study on the Effect of Emissivity for Estimation of the Surface Temperature from Drone-based Thermal Images (드론 열화상 화소값의 타겟 온도변환을 위한 방사율 영향 분석)

  • Jo, Hyeon Jeong;Lee, Jae Wang;Jung, Na Young;Oh, Jae Hong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.1
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    • pp.41-49
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    • 2022
  • Recently interests on the application of thermal cameras have increased with the advance of image analysis technology. Aside from a simple image acquisition, applications such as digital twin and thermal image management systems have gained popularity. To this end, we studied the effect of emissivity on the DN (Digital Number) value in the process of derivation of a relational expression for converting DN to an actual surface temperature. The DN value is a number representing the spectral band value of the thermal image, and is an important element constituting the thermal image data. However, the DN value is not a temperature value indicating the actual surface temperature, but a brightness value indicating high and low heat as brightness, and has a non-linear relationship with the actual surface temperature. The reliable relationship between DN and the actual surface temperature is critical for a thermal image processing. We tested the relationship between the actual surface temperature and the DN value of the thermal image, and then the radiation adjustment was performed to better estimate actual surface temperatures. As a result, the relation graph between the actual surface temperature and the DN value similarly show linear pattern with the relation graph between the radiation-controlled non-contact thermometer and the DN value. And the non-contact temperature after adjusting the emissivity was closer to the actual surface temperature than before adjusting the emissivity.

Mechanism Design of Cane-like Passive Type Walking Aid For the Elderly Using 3-RPS Parallel Manipulator (3-RPS 평형기구를 이용한 노인용 지팡이형 보행보조기기 메커니즘 개발)

  • Kim, Jeong-Hun;Jang, Dae-jin;Park, Tae-Wook;Yang, Hyun-Seok;Lee, Sang-Moo
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.725-730
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    • 2004
  • This paper has regarded mechanism design of cane-like passive type walking aid for the elderly using 3-RPS parallel manipulator. First, gait patterns of the elderly have been experimented. By means of motion capturing and image processing, we decided loaded forces and places of the cane when the elderly walked with a cane. Using these results we have developed a passive type walking aid. Second, the walking pattern has been simulated using dynamic analysis program, ADAMS and we find out the similarity between the real walking and the simulated walking. Finally after assuring the similarity, with adjusting the new mechanism design to the simulated walking we will decide whether the walking aid is safe and stable when the elderly walks with this cane-like walking aid. This paper will be basis for the development of the mechanism design applying 3-RPS parallel manipulator.

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Semiautomated Analysis of Data from an Imaging Sonar for Fish Counting, Sizing, and Tracking in a Post-Processing Application

  • Kang, Myoung-Hee
    • Fisheries and Aquatic Sciences
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    • v.14 no.3
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    • pp.218-225
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    • 2011
  • Dual frequency identification sonar (DIDSON) is an imaging sonar that has been used for numerous fisheries investigations in a diverse range of freshwater and marine environments. The main purpose of DIDSON is fish counting, fish sizing, and fish behavioral studies. DIDSON records video-quality data, so processing power for handling the vast amount of data with high speed is a priority. Therefore, a semiautomated analysis of DIDSON data for fish counting, sizing, and fish behavior in Echoview (fisheries acoustic data analysis software) was accomplished using testing data collected on the Rakaia River, New Zealand. Using this data, the methods and algorithms for background noise subtraction, image smoothing, target (fish) detection, and conversion to single targets were precisely illustrated. Verification by visualization identified the resulting targets. As a result, not only fish counts but also fish sizing information such as length, thickness, perimeter, compactness, and orientation were obtained. The alpha-beta fish tracking algorithm was employed to extract the speed, change in depth, and the distributed depth relating to fish behavior. Tail-beat pattern was depicted using the maximum intensity of all beams. This methodology can be used as a template and applied to data from BlueView two-dimensional imaging sonar.

Hierarchical Clustering of Symbolic Objects based on Asymmetric Proximity (비대칭적 유사도 기반의 심볼릭 객체의 계층적 클러스터링)

  • Oh, Seung-Joon;Park, Chan-Woong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.6
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    • pp.729-734
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    • 2012
  • Clustering analysis has been widely used in numerous applications like pattern recognition, data analysis, intrusion detection, image processing, bioinformatics and so on. Much of previous work has been based on the numeric data only. However, symbolic data analysis has emerged to deal with variables that can have intervals, histograms, and even functions as values. In this paper, we propose a non symmetric proximity based clustering approach for symbolic objects. A method for clustering symbolic patterns based on the average similarity value(ASV) is explored. The results of the proposed clustering method differ from those of the existing methods and the results are very encouraging.