• Title/Summary/Keyword: recognized images

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Traffic flow measurement system using image processing

  • Hara, Takaaki;Akizuki, Kageo;Kawamura, Mamoru
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.426-439
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    • 1996
  • In this paper, we propose a simple algorithm to calculate the numbers of the passing cars by using an image processing sensor for the digital black and white images with 256 tone level. Shadow is one of the most troublesome factor in image processing. By differencing the tone level, we cannot discriminate between the body of the car and its shadow. In our proposed algorithm, the area of the shadow is excluded by recognizing the position of each traffic lane. For real-time operation and simple calculation, two lines of the tone level are extracted and the existences of cars are recognized. In the experimental application on a high-way, the recognition rate of the real-time operation is more than 94%.

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Tracking of Moving Objects Using Morphological Segmentation, Statistical Moments and Hough Transform

  • Ahmad, Muhammad Bilal;Chang, Min-Hyuk;Park, Jong-An
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1377-1381
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    • 2003
  • This paper describes real time object tracking of 3D objects in 2D image sequences. The moving objects are segmented from the image sequence using morphological operations. The moving objects are segmented by the method of differential image followed by the process of morphological dilation. The moving objects are recognized and tracked using statistical moments. The direction of moving objects are determined by the Hough transform. The straight lines in the moving objects are found with the help of Hough transform. The direction of the moving object is calculated from the orientation of the straight lines in the direction of the principal axes of the moving objects. The direction of the moving object and the displacement of the object in the image sequence is used to calculate the velocity of the moving objects. The simulation results of the proposed method are promising on the test images.

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Recognition of the movement of a 3D object (물체의 3차원 운동방향 인식)

  • Lee, Hyun-Jung;Cho, Dong-Sub
    • Proceedings of the KIEE Conference
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    • 1990.11a
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    • pp.470-473
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    • 1990
  • In this thesis, the recognition method of the movement of an 3D object is presented. The information about the movement of a 3D object is used to recognize the object. There are 2 kinds of movements which are translation and rotation. A difference picture is obtained from a sequence of images of a moving object or a scene which is taken by a monocular stationary observer. The 3D movement of an object is recognized by the Artificial Neural Network(ANN) using the difference picture.

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Enhanced Independent Component Analysis of Temporal Human Expressions Using Hidden Markov model

  • Lee, J.J.;Uddin, Zia;Kim, T.S.
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.487-492
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    • 2008
  • Facial expression recognition is an intensive research area for designing Human Computer Interfaces. In this work, we present a new facial expression recognition system utilizing Enhanced Independent Component Analysis (EICA) for feature extraction and discrete Hidden Markov Model (HMM) for recognition. Our proposed approach for the first time deals with sequential images of emotion-specific facial data analyzed with EICA and recognized with HMM. Performance of our proposed system has been compared to the conventional approaches where Principal and Independent Component Analysis are utilized for feature extraction. Our preliminary results show that our proposed algorithm produces improved recognition rates in comparison to previous works.

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A Human Activity Recognition System Using ICA and HMM

  • Uddin, Zia;Lee, J.J.;Kim, T.S.
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.499-503
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    • 2008
  • In this paper, a novel human activity recognition method is proposed which utilizes independent components of activity shape information from image sequences and Hidden Markov Model (HMM) for recognition. Activities are represented by feature vectors from Independent Component Analysis (ICA) on video images, and based on these features; recognition is achieved by trained HMMs of activities. Our recognition performance has been compared to the conventional method where Principle Component Analysis (PCA) is typically used to derive activity shape features. Our results show that superior recognition is achieved with our proposed method especially for activities (e.g., skipping) that cannot be easily recognized by the conventional method.

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Recognition of Car License Plates Using Fuzzy Clustering Algorithm

  • Cho, Jae-Hyun;Lee, Jong-Hee
    • Journal of information and communication convergence engineering
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    • v.6 no.4
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    • pp.444-447
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    • 2008
  • In this paper, we proposed the recognition system of car license plates to mitigate traffic problems. The processing sequence of the proposed algorithm is as follows. At first, a license plate segment is extracted from an acquired car image using morphological features and color information, and noises are eliminated from the extracted license plate segment using line scan algorithm and Grassfire algorithm, and then individual codes are extracted from the license plate segment using edge tracking algorithm. Finally the extracted individual codes are recognized by an FCM algorithm. In order to evaluate performance of segment extraction and code recognition of the proposed method, we used 100 car images for experiment. In the results, we could verify the proposed method is more effective and recognition performance is improved in comparison with conventional car license plate recognition methods.

A Study on Brand Image Preference and Fashion Advertising Strategy (상표이미지 선호도와 패션 광고 전략에 관한 연구 - 여대생을 중심으로 -)

  • Kim Moon Jin;Rim Sook Ja
    • Journal of the Korean Society of Clothing and Textiles
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    • v.13 no.3 s.31
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    • pp.197-206
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    • 1989
  • This study was to investigate brand images of ladies wear and the effects of fashion advertisements, and to determine the difference of brand image preference and the effects of fashion advertising by clothing life style. 421 subjects were gathered through stratified sampling method and, for data analysis, frequency distribution, $x^2-test$, Cronbach'$\alpha$, ANOVA, Duncan's multiple Range test, Multiple Dimentional Scaling (M.D.S.), Factor analysis, Cluster analysis, were conducted. The results are as follows; 1. In image formation process, feminine as formal image, manish as casual image, were recognized. 2. Four factors were determined for analysis of clothing life styles and with these factors five different clothing life style groups were classified. 3. There was a meaningful difference between clothing life style and brand image preference, and also between clothing life style and the effects of fashion advertisement. From these findings, general and specific fashion advertising strategies are proposed.

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Table Detection from Document Image using Vertical Arrangement of Text Blocks

  • Tran, Dieu Ni;Tran, Tuan Anh;Oh, Aran;Kim, Soo Hyung;Na, In Seop
    • International Journal of Contents
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    • v.11 no.4
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    • pp.77-85
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    • 2015
  • Table detection is a challenging problem and plays an important role in document layout analysis. In this paper, we propose an effective method to identify the table region from document images. First, the regions of interest (ROIs) are recognized as the table candidates. In each ROI, we locate text components and extract text blocks. After that, we check all text blocks to determine if they are arranged horizontally or vertically and compare the height of each text block with the average height. If the text blocks satisfy a series of rules, the ROI is regarded as a table. Experiments on the ICDAR 2013 dataset show that the results obtained are very encouraging. This proves the effectiveness and superiority of our proposed method.

Bin Picking method using stereo vision (스테레오 비젼을 이용한 Bin Picking Method)

  • 주기세;한민홍
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.692-698
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    • 1993
  • This paper presents a Bin-Picking method in which robot recognizes the positions and orientations of jumbled objects placed in a bin, then picks up distinctive objects from the top of the jumble. The jumbled objects are recognized comparing the characteristics extracted from stereo images with those in the CAD data. The 3-D information is obtained using the bipartite-matching method which compares image of one camera with the image of the other camera Then the robot picks up the object which will cause the least amount of disturbance to the jumble, and places it at a predetermined place. This paper contributes to the basic study of Bin-Picking, and can be used in an automatic assembly system without using part sorting or orienting devices.

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Mimemodes cribratus (Reitter) (Coleoptera: Cucujoidea: Monotomidae) New to Korea and a Key to Korean Monotomid Species (큰머리톱가슴긴고목벌레의 국내 첫 보고 및 한국산 톱가슴긴고목벌레과의 종 분류 검색표)

  • Lee, Seung-Gyu;Kim, Moo-Sung;Lim, Jongok;Kim, Il-Kwon
    • Korean journal of applied entomology
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    • v.57 no.2
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    • pp.65-68
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    • 2018
  • Mimemodes cribratus (Reitter) is newly recognized from Korea. The present study includes a redescription, images of habitus and diagnostic characters of the species. In addition, a key to Korean species of Monotomidae is provided.