• Title/Summary/Keyword: robust extraction

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Sequence Images Registration by using KLT Feature Detection and Tracking (KLT특징점 검출 및 추적에 의한 비디오영상등록)

  • Ochirbat, Sukhee;Park, Sang-Eon;Shin, Sung-Woong;Yoo, Hwan-Hee
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.2
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    • pp.49-56
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    • 2008
  • Image registration is one of the critical techniques of image mosaic which has many applications such as generating panoramas, video monitoring, image rendering and reconstruction, etc. The fundamental tasks of image registration are point features extraction and tracking which take much computation time. KLT(Kanade-Lucas-Tomasi) feature tracker has proposed for extracting and tracking features through image sequences. The aim of this study is to demonstrate the usage of effective and robust KLT feature detector and tracker for an image registration using the sequence image frames captured by UAV video camera. In result, by using iterative implementation of the KLT tracker, the features extracted from the first frame of image sequences could be successfully tracked through all frames. The process of feature tracking in the various frames with rotation, translation and small scaling could be improved by a careful choice of the process condition and KLT pyramid implementation.

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Vehicle Recognition using NMF in Urban Scene (도심 영상에서의 비음수행렬분해를 이용한 차량 인식)

  • Ban, Jae-Min;Lee, Byeong-Rae;Kang, Hyun-Chul
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.7C
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    • pp.554-564
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    • 2012
  • The vehicle recognition consists of two steps; the vehicle region detection step and the vehicle identification step based on the feature extracted from the detected region. Features using linear transformations have the effect of dimension reduction as well as represent statistical characteristics, and show the robustness in translation and rotation of objects. Among the linear transformations, the NMF(Non-negative Matrix Factorization) is one of part-based representation. Therefore, we can extract NMF features with sparsity and improve the vehicle recognition rate by the representation of local features of a car as a basis vector. In this paper, we propose a feature extraction using NMF suitable for the vehicle recognition, and verify the recognition rate with it. Also, we compared the vehicle recognition rate for the occluded area using the SNMF(sparse NMF) which has basis vectors with constraint and LVQ2 neural network. We showed that the feature through the proposed NMF is robust in the urban scene where occlusions are frequently occur.

A Study on a Diagnosis System for HSR Turnout Systems (II) (고속철도 분기기 시스템 진단 시스템에 관한 연구(II))

  • Kim, Youngseok;Yoon, Yeonjoo;Back, Inchul;Ryu, Youngtae;Han, Hyunsu;Hwang, Ankyu;Kang, Hyungseok;Lee, Jongwoo
    • Journal of the Korean Society for Railway
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    • v.20 no.2
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    • pp.223-233
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    • 2017
  • The railway turnout system is one of the most important systems that set train routes. Turnout system integrity should be guaranteed for robust train operation. To diagnose the turnout system status, LVDT and accelerometers are installed on a turnout system in a high speed line. The LVDT and accelerometers produce signals containing physical meaning of the turnout systems. The LVDT produces the displacement of the rail gauge and vibration when point moving or a train passes on turnout systems and the accelerometer produces impact forces induced by wheel sets. We performed data extraction from the measured signals and parameterized the extracted signals into meaningful quantities. The parameters are used for classifying whether the turnout status is normal. We proposed two methods for the classification, one uses probabilistic distribution and the other artificial neuron networks. The probabilistic distribution is used for the parameter being classified by the quantities and the artificial neuron networks for the form classification. Finally, we show how to learn the normal status of a turnout system.

Confocal Microscopy Image Segmentation and Extracting Structural Information for Morphological Change Analysis of Dendritic Spine (수상돌기 소극체의 형태변화 분석을 위한 공초점현미경 영상 분할 및 구조추출)

  • Son, Jeany;Kim, Min-Jeong;Kim, Myoung-Hee
    • Journal of the Korea Society for Simulation
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    • v.17 no.4
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    • pp.167-174
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    • 2008
  • The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.

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Performance Comparison of Skin Color Detection Algorithms by the Changes of Backgrounds (배경의 변화에 따른 피부색상 검출 알고리즘의 성능 비교)

  • Jang, Seok-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.3
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    • pp.27-35
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    • 2010
  • Accurately extracting skin color regions is very important in various areas such as face recognition and tracking, facial expression recognition, adult image identification, health-care, and so forth. In this paper, we evaluate the performances of several skin color detection algorithms in indoor environments by changing the distance between the camera and the object as well as the background colors of the object. The distance is from 60cm to 120cm and the background colors are white, black, orange, pink, and yellow, respectively. The algorithms that we use for the performance evaluation are Peer algorithm, NNYUV, NNHSV, LutYUV, and Kimset algorithm. The experimental results show that NNHSV, NNYUV and LutYUV algorithm are stable, but the other algorithms are somewhat sensitive to the changes of backgrounds. As a result, we expect that the comparative experimental results of this paper will be used very effectively when developing a new skin color extraction algorithm which are very robust to dynamic real environments.

A Study on Extraction of Irregular Iris Patterns (비정형 홍채 패턴 분리에 관한 연구)

  • Won, Jung-Woo;Cho, Seong-Won;Kim, Jae-Min;Baik, Kang-Chul
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.2
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    • pp.169-174
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    • 2008
  • Recently, biometric systems are of interest for the reliable security system. Iris recognition technology is one of the biometric system with the highest reliability. Various iris recognition methods have been proposed for automatic personal identification and verification. These methods require accurate iris segmentation for successful processing because the iris is a small part of an acquired image. The iris boundaries have been parametrically modeled and subsequently detected by circles or parabolic arcs. Since the iris boundaries have a wide range of edge contrast and irregular border shapes, the assumption that they can be fit to circles or parabolic arcs is not always valid. In some cases, the shape of a dilated pupil is slightly different from a constricted one. This is especially true when the pupil has an irregular shape. This is why this research is important. This paper addresses how to accurately detect iris boundaries for improved iris recognition, which is robust to noises.

Green Chroma Keying for Robot Performances in Public Places (공공장소에서 로봇 공연용 그린 크로마키 합성)

  • Hwang, Heesoo
    • Journal of the Korea Convergence Society
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    • v.8 no.7
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    • pp.7-13
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    • 2017
  • Robot performances in public places are conducted for the purpose of promoting robot technology and inducing interest in events, exhibitions, and streets instead of dedicated stages. This paper extracts robot images in real time from a robot operation in front of a green chroma key cloth, and synthesizes them on various stage images. A simple and robust method for extracting a foreground robot from a chroma key background without a user's preset is proposed. After increasing the color difference between the background and the foreground, this method automatically removes the background based on the histogram of the difference information, thereby eliminating the need for a user's preset. The simulation shows 98.8% of foreground extraction rate and experimental results demonstrate that the robots can effectively be extracted from the background.

Development of an experimental model for radiation-induced inhibition of cranial bone regeneration

  • Jung, Hong-Moon;Lee, Jeong-Eun;Lee, Seoung-Jun;Lee, Jung-Tae;Kwon, Tae-Yub;Kwon, Tae-Geon
    • Maxillofacial Plastic and Reconstructive Surgery
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    • v.40
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    • pp.34.1-34.8
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    • 2018
  • Background: Radiation therapy is widely employed in the treatment of head and neck cancer. Adverse effects of therapeutic irradiation include delayed bone healing after dental extraction or impaired bone regeneration at the irradiated bony defect. Development of a reliable experimental model may be beneficial to study tissue regeneration in the irradiated field. The current study aimed to develop a relevant animal model of post-radiation cranial bone defect. Methods: A lead shielding block was designed for selective external irradiation of the mouse calvaria. Critical-size calvarial defect was created 2 weeks after the irradiation. The defect was filled with a collagen scaffold, with or without incorporation of bone morphogenetic protein 2 (BMP-2) (1 ㎍/ml). The non-irradiated mice treated with or without BMP-2-included scaffold served as control. Four weeks after the surgery, the specimens were harvested and the degree of bone formation was evaluated by histological and radiographical examinations. Results: BMP-2-treated scaffold yielded significant bone regeneration in the mice calvarial defects. However, a single fraction of external irradiation was observed to eliminate the bone regeneration capacity of the BMP-2-incorporated scaffold without influencing the survival of the animals. Conclusion: The current study established an efficient model for post-radiation cranial bone regeneration and can be applied for evaluating the robust bone formation system using various chemokines or agents in unfavorable, demanding radiation-related bone defect models.

Recognition of Unconstrained Handwritten Numerals using Modified Chaotic Neural Networks (수정된 카오스 신경망을 이용한 무제약 서체 숫자 인식)

  • 최한고;김상희;이상재
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.1
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    • pp.44-52
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    • 2001
  • This paper describes an off-line method for recognizing totally unconstrained handwritten digits using modified chaotic neural networks(MCNN). The chaotic neural networks(CNN) is modified to be a useful network for solving complex pattern problems by enforcing dynamic characteristics and learning process. Since the MCNN has the characteristics of highly nonlinear dynamics in structure and neuron itself, it can be an appropriate network for the robust classification of complex handwritten digits. Digit identification starts with extraction of features from the raw digit images and then recognizes digits using the MCNN based classifier. The performance of the MCNN classifier is evaluated on the numeral database of Concordia University, Montreal, Canada. For the relative comparison of recognition performance, the MCNN classifier is compared with the recurrent neural networks(RNN) classifier. Experimental results show that the classification rate is 98.0%. It indicates that the MCNN classifier outperforms the RNN classifier as well as other classifiers that have been reported on the same database.

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A Study on Recognition of Both of New & Old Types of Vehicle Plate (신, 구 차량 번호판 통합 인식에 관한 연구)

  • Han, Kun-Young;Woo, Young-Woon;Han, Soo-Whan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.10
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    • pp.1987-1996
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    • 2009
  • Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.