• Title/Summary/Keyword: Real-time Segmentation

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An Algorithm for Segmenting the License Plate Region of a Vehicle Using a Color Model (차량번호판 색상모델에 의한 번호판 영역분할 알고리즘)

  • Jun Young-Min;Cha Jeong-Hee
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.43 no.2 s.308
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    • pp.21-32
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    • 2006
  • The license plate recognition (LPR) unit consists of the following core components: plate region segmentation, individual character extraction, and character recognition. Out of the above three components, accuracy in the performance of plate region segmentation determines the overall recognition rate of the LPR unit. This paper proposes an algorithm for segmenting the license plate region on the front or rear of a vehicle in a fast and accurate manner. In the case of the proposed algorithm images are captured on the spot where unmanned monitoring of illegal parking and stowage is performed with a variety of roadway environments taken into account. As a means of enhancing the segmentation performance of the on-the-spot-captured images of license plate regions, the proposed algorithm uses a mathematical model for license plate colors to convert color images into digital data. In addition, this algorithm uses Gaussian smoothing and double threshold to eliminate image noises, one-pass boundary tracing to do region labeling, and MBR to determine license plate region candidates and extract individual characters from the determined license plate region candidates, thereby segmenting the license plate region on the front or rear of a vehicle through a verification process. This study contributed to addressing the inability of conventional techniques to segment the license plate region on the front or rear of a vehicle where the frame of the license plate is damaged, through processing images in a real-time manner, thereby allowing for the practical application of the proposed algorithm.

Hybrid Multicast/Broadcast Algorithm for Highly-Demanded Video Services with Low Complexity (Highly-Demanded 비디오 서비스를 위한 낮은 복잡도의 혼합 멀티캐스트/브로드캐스트 알고리즘)

  • Li, Can;Bahk, Sae-Woong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.1B
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    • pp.101-110
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    • 2011
  • With the deployment of broadband networking technology, many clients are enabled to receive various Video on Demand (VoD) services. To support many clients, the network should be designed by considering the following factors: viewer's waiting time, buffer requirement at each client, number of channel required for video delivery, and video segmentation complexity. Among the currently available VoD service approaches, the Polyharmonic and Staircase broadcasting approaches show best performance with respect to each viewer's waiting time and buffer requirement, respectively. However, these approaches have the problem of dividing a video into too many segments, which causes very many channels to be managed and used at a time. To overcome this problem, we propose Polyharmonic-Staircase-Staggered (PSS) broadcasting approach that uses the Polyharmonic and Staircase approaches for the head part transmission and the Staggered approach for the tail part transmission. It is simple and bandwidth efficient. The numerical results demonstrate that our approach shows viewer's waiting time is comparable to that in the Harmonic approach with a slight increase in the bandwidth requirement, and saves the buffer requirement by about 60\% compared to the Harmonic broadcasting approach by simply adjusting the video partitioning coefficient factor. More importantly, our approach shows the best performance in terms of the number of segments and the number of channels managed and used simultaneously, which is a critical factor in real operation of VoD services. Lastly, we present how to configure the system adaptively according to the video partitioning coefficient.

Finding Stop Position of Taxis using IoV data and road segment algorithm (IoV 데이터와 도로 분할 알고리즘을 이용한 택시 정차위치 파악)

  • Lim, Dong-jin;Onueam, Athita;Jung, Han-min
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.590-592
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    • 2018
  • Taxis that are illegally parked on the road to catch customer can cause traffic congestion and sometimes cause traffic accidents. Stop position of taxis is determined by the long term experience of taxi drivers. In this study, We provide information to taxi drivers and customer who visit in first time through finding stop position of taxis by time. To do this, we used the Internet of Vehicle (IoV) data collected from sensors installed in 40 taxis. Previous studies attempted by forming a cluster around a taxi. Since this method is centered on a taxi, the position of the cluster changes depending on the location of the taxi. In this study, we use a road segmentation algorithm to solve these problems. Unlike the previous studies, since the cluster is formed around the road, the position of the cluster is fixed and it is not affected by the number of taxis, so it is possible to grasp the stop position in real time. The road segmentation is made up of 30m units, and map the taxi location data divided into hourly, weekday, and weekend to the nearest point. As a result of the mapping, it was difficult to see a big difference in the time of week because there were few taxis to operate on weekends, but in case of weekdays, the difference of stop position between the commute time zone and the night time zone was confirmed. The results of this study suggest that it will be possible to propose the prevention of taxi illegally driving taxi and the location of the taxi stand.

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A Study on the Generation of Ultrasonic Binary Image for Image Segmentation (Image segmentation을 위한 초음파 이진 영상 생성에 관한 연구)

  • Choe, Heung-Ho;Yuk, In-Su
    • Journal of Biomedical Engineering Research
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    • v.19 no.6
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    • pp.571-575
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    • 1998
  • One of the most significant features of diagnostic ultrasonic instruments is to provide real time information of the soft tissues movements. Echocardiogram has been widely used for diagnosis of heart diseases since it is able to show real time images of heart valves and walls. However, the currently used ultrasonic images are deteriorated due to presence of speckle noises and image dropout. Therefore, it is very important to develop a new technique which can enhance ultrasonic images. In this study, a technique which extracts enhanced binary images in echocardiograms was proposed. For this purpose, a digital moving image file was made from analog echocardiogram, then it was stored as 8-bit gray-level for each frame. For an efficient image processing, the region containing the heat septum and tricuspid valve was selected as the region of interest(ROI). Image enhancement filters and morphology filters were used to reduce speckle noises in the images. The proposed procedure in this paper resulted in binary images with enhanced contour compared to those form the conventional threshold technique and original image processing technique which can be further implemented for the quantitative analysis of the left ventricular wall motion in echocardiogram by easy detection of the heart wall contours.

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Customer-Centric CRM Implementation Case Study (고객중심의 CRM 구축비교 사례연구)

  • Lee, Ho-Seoub
    • Management & Information Systems Review
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    • v.23
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    • pp.25-40
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    • 2007
  • In the highly competitive and divers world of financial market, customer is the single most important factor to company's survival. Especially, creating a relationship with valued customers is a key to success. CRM provides the mean to retain high value customers. It takes a prospect of what customers expect. Utilizing those knowledge can help the products and service meet the customers' needs, thereby maximizing customer satisfaction and company's profit. In this report, I am going to suggest a few ways to develop successful CRM in the life insurance industry. First, CRM should innovate the way of communication to keep pace with Web 2.0 era. In other words, the customer's needs should be caught by real-time communication than traditional off-line market research. Thus, the functionality and specification of products can be decided by customer's direct choice so that the customers are able to purchase the understanding and experience of the products. Second, CRM project should consider whether the initial strategy plan can promise the stable growth of customer at the first step. When planning strategy, the project needs to identify what customer wants and how to fulfill the needs with stable growth of the customer. In addition, the CRM should be developed by realizing that customer centric benefits ultimately guarantee the growth of the organization. Third, CRM systems should enhance the organization's ability to take the customer's insight in a 360 degree view and to capture the voice of the customer directly. In order to develop the best matched product package, more precise customer segmentation should be ahead of market segmentation strategy. Forth, the biggest reward from CRM will be a customer royalty program. Many successful banks are already planning and practicing customer royalty strategy. A comprehensive analysis of customers and their behavior allow organization to identify high value potential customers' needs and determine a strategy required to meet those needs. Even life insurance companies such as Prudential Korea are developing products designed for royal customers. Fifth, understanding and managing the experience of customer called Customer Experience Management also can increase customer satisfaction. Measuring only customers' experience and adapting it to marketing strategy make products position in the gap between the customers' expectation and experience not required by market. A key component of CEM is its application across all organizational functions. At last, the direction of change and development of CRM can be defined from the conceptualization of information technology represented by Ubiquitous and Web 2.0. Instead of just managing customer information, companies should take the initiative in personalized system with customer oriented strategy. Furthermore, with the regular communication between CRM stakeholders (Sales-Marketing-IT), customer's demand should be directly reflected to enterprise strategy in real time.

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Separation of Touching Pigs using YOLO-based Bounding Box (YOLO 기반 외곽 사각형을 이용한 근접 돼지 분리)

  • Seo, J.;Ju, M.;Choi, Y.;Lee, J.;Chung, Y.;Park, D.
    • Journal of Korea Multimedia Society
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    • v.21 no.2
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    • pp.77-86
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    • 2018
  • Although separation of touching pigs in real-time is an important issue for a 24-h pig monitoring system, it is challenging to separate accurately the touching pigs in a crowded pig room. In this study, we propose a separation method for touching pigs using the information generated from Convolutional Neural Network(CNN). Especially, we apply one of the CNN-based object detection methods(i.e., You Look Only Once, YOLO) to solve the touching objects separation problem in an active manner. First, we evaluate and select the bounding boxes generated from YOLO, and then separate touching pigs by analyzing the relations between the selected bounding boxes. Our experimental results show that the proposed method is more effective than widely-used methods for separating touching pigs, in terms of both accuracy and execution time.

Implementation of the Squared-Error Pattern Clustering Processor Using the Residue Number System (剩餘數體系를 이용한 자승오차 패턴 클러스터링 프로세서의 실현)

  • Kim, Hyeong-Min;Cho, Won-Kyung
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.2
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    • pp.87-93
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    • 1989
  • Squared-error Pattern Clustering algorithm used in unsupervised pattern recognition and image processing application demands substantial processing time for operation of feature vector matrix. So, this paper propose the fast squared-error Pattern Clustering Processor using the Residue Number System which have been the nature of parallel processing and pipeline. The proposed Squared-error Pattern Clustering Processor illustrate satisfiable error rate for Cluster number which can be divide meaningful region and about 200 times faster than 80287 coprocessor from experiments result of image segmentation. In this result, it is useful to real-time processing application for large data.

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Matching for Cylinder Shape in Point Cloud Using Random Sample Consensus (Random Sample Consensus를 이용한 포인트 클라우드 실린더 형태 매칭)

  • Jin, YoungHoon
    • Journal of KIISE
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    • v.43 no.5
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    • pp.562-568
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    • 2016
  • Point cloud data can be expressed in a specific coordinate system of a data set with a large number of points, to represent any form that generally has different characteristics in the three-dimensional coordinate space. This paper is aimed at finding a cylindrical pipe in the point cloud of the three-dimensional coordinate system using RANSAC, which is faster than the conventional Hough Transform method. In this study, the proposed cylindrical pipe is estimated by combining the results of parameters based on two mathematical models. The two kinds of mathematical models include a sphere and line, searching the sphere center point and radius in the cylinder, and detecting the cylinder with straightening of center. This method can match cylindrical pipe with relative accuracy; furthermore, the process is rapid except for normal estimation and segmentation. Quick cylinders matching could benefit from laser scanning and reverse engineering construction sectors that require pipe real-time estimates.

A CORBA-Based Collaborative Work Supported Medical Image Analysis and Visualization System (코바기반 협업지원 의료영상 분석 및 가시화 시스템)

  • Chun, Jun-Chul;Son, Jae-Gi
    • The KIPS Transactions:PartD
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    • v.10D no.1
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    • pp.109-116
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    • 2003
  • In this paper, a CORBA-based collaborative medical image analysis and visualization system, which provides high accessibility and usability of the system for the users on distributed environment is introduced. The system allows us to manage datasets and manipulates medical images such as segmentation and volume visualization of computed geometry from biomedical images in distributed environments. Using Bayesian classification technique and an active contour model the system provides classification results of medical images or boundary information of specific tissue. Based on such information, the system can create real time 3D volume model from medical imagery. Moreover, the developed system supports collaborative work among multiple users using broadcasting and synchronization mechanisms. Since the system is developed using Java and CORBA, which provide distributed programming, the remote clients can access server objects via method invocation, without knowing where the distributed objects reside or what operating system it executes on.

Noise-robust Hand Region Segmentation In RGB Color-based Real-time Image (RGB 색상 기반의 실시간 영상에서 잡음에 강인한 손영역 분할)

  • Yang, Hyuk Jin;Kim, Dong Hyun;Seo, Yeong Geon
    • Journal of Digital Contents Society
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    • v.18 no.8
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    • pp.1603-1613
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    • 2017
  • This paper proposes a method for effectively segmenting the hand region using a widely popular RGB color-based webcam. This performs the empirical preprocessing method four times to remove the noise. First, we use Gaussian smoothing to remove the overall image noise. Next, the RGB image is converted into the HSV and the YCbCr color model, and global fixed binarization is performed based on the statistical value for each color model, and the noise is removed by the bitwise-OR operation. Then, RDP and flood fill algorithms are used to perform contour approximation and inner area fill operations to remove noise. Finally, ROI (hand region) is selected by eliminating noise through morphological operation and determining a threshold value proportional to the image size. This study focuses on the noise reduction and can be used as a base technology of gesture recognition application.