• Title/Summary/Keyword: 추적 정확도 향상

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Real-time Moving Object Recognition and Tracking Using The Wavelet-based Neural Network and Invariant Moments (웨이블릿 기반의 신경망과 불변 모멘트를 이용한 실시간 이동물체 인식 및 추적 방법)

  • Kim, Jong-Bae
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.4
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    • pp.10-21
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    • 2008
  • The present paper propose a real-time moving object recognition and tracking method using the wavelet-based neural network and invariant moments. Candidate moving region detection phase which is the first step of the proposed method detects the candidate regions where a pixel value changes occur due to object movement based on the difference image analysis between continued two image frames. The object recognition phase which is second step of proposed method recognizes the vehicle regions from the detected candidate regions using wavelet neurual-network. From object tracking Phase which is third step the recognized vehicle regions tracks using matching methods of wavelet invariant moments bases to recognized object. To detect a moving object from image sequence the candidate regions detection phase uses an adaptive thresholding method between previous image and current image as result it was robust surroundings environmental change and moving object detections were possible. And by using wavelet features to recognize and tracking of vehicle, the proposed method decrease calculation time and not only it will be able to minimize the effect in compliance with noise of road image, vehicle recognition accuracy became improved. The result which it experiments from the image which it acquires from the general road image sequence and vehicle detection rate is 92.8%, the computing time per frame is 0.24 seconds. The proposed method can be efficiently apply to a real-time intelligence road traffic surveillance system.

A Study on Improving Accuracy of Subway Location Tracking using WiFi Fingerprinting (WiFi 핑거프린트를 이용한 지하철 위치 추적 정확성 향상을 위한 연구)

  • An, Taeki;Ahn, Chihyung;Nam, Myungwoo;Park, Jinhong;Lee, Youngseok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.1
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    • pp.1-8
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    • 2016
  • In this study, an WiFi fingerprinting method based on the k-nn algorithm was applied to improve the accuracy of location tracking of a moving train on a platform and evaluate the performance to minimize the estimation error of location tracking. The data related to the position of the moving train are monitored by the control center for trains and used widely for the safety and comfort of passengers. The train location tracking methods based on WiFi installed by telecom companies were evaluated. In this study, a simulator was developed to consider the environments of two cases; in already installed WiFi devices and new installed WiFi devices. The developed simulator can simulate the localized estimation of the position under a variety of conditions, such as the number of WiFi devices, the area of platform and entry velocity of train. To apply location tracking algorithms, a k-nn algorithm and fuzzy k-nn algorithm were applied selectively according to the underlying condition and also four distance measurement algorithms were applied to compare the error of location tracking. In conclusion, the best method to estimate train location tracking is a combination of the k-nn algorithm and Minkoski distance measurement at a 0.5m grid unit and 8 WiFi AP installed.

Standardization of Identification-number for Processed Food in Food-traceability-system (가공식품에 대한 이력추적관리번호 부여체계의 표준화 방안)

  • Choi, Joon-Ho
    • Journal of Food Hygiene and Safety
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    • v.27 no.2
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    • pp.194-201
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    • 2012
  • Facing a number of global food-related accidents, the concept and system for food traceability have been designed and introduced in many countries to manage the food-safety risks. To connect and harmonize the various food traceability-information in food traceability system according to the food supply chain, the coding system of identification-number for food-traceability has to be standardized. The GTIN (Global Trade Item Number) barcode system which has been globally standardized and implemented, is reviewed with the mandatory food-labeling regulation in expiration date of processed foods. The integration of GTIN-13 bar-code system for food-traceability is a crucial factor to expand its function in the food-related industrial areas. In this literature, the standard coding system of identification-number for food-traceability is proposed with 20 digit coding number which is combined with GTIN-13 bar-code (13 digit), expiration date (6 digit), and additional classification code (1 digit). This proposed standard coding system for identification-number has a several advantages in application for prohibiting the sale of hazard goods, food-recall, and inquiring food traceability-information. And also, this proposed coding system could enhance the food traceability system by communicating and harmonizing the information with the national network such as UNI-PASS and electronic Tax-invoice system. For the global application, the identification-number for food-traceability needs to be cooperated with the upcoming global standards such as GTIN-128 bar-code and GS1 DataBar.

Design and Implementation of Real Time Locating System for Efficient Vehicle Pooling in Port Terminal (항만 터미널 내 차량의 효율적 풀링을 위한 실시간 위치 측정 시스템 설계 및 구현)

  • Son, Sang-Hyun;Cho, Hyun-Tae;Beak, Yun-Ju
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.9
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    • pp.2056-2063
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    • 2012
  • In a port terminal, containers are stored and transshipped by yard tractors and crane vehicles. For operation efficiency of the terminal, location information of these vehicles is an essential factor. However, most of port terminals try to estimate location of these assets using indirect methods such as event tracking of shipping or unshipping containers. Because these kinds of events are rarely occurred, location of the event includes seriously locating error compared to a real location of vehicle. In this paper, we propose a real-time asset tracking system to obtain accurate and reliable location of terminal assets. The proposed system overcomes a location estimation error caused by container stacks which interrupt wireless communication. In order to mitigate uncertainty and increase accuracy of location estimation, we designed hardwares and multi-step locating system to resolve additional preblems. We implemented system components, and installed these at a port environment for evaluation. The result shows superiority of the system that the accuracy is approximately 5.87 meters (CEP).

Convergence study on the change of cognitive function through the intentional finger movement (의식적 손가락 움직임이 인지기능 변화에 미치는 융합연구)

  • Kim, Kyung-Yoon;Bae, Seahyun
    • Journal of the Korea Convergence Society
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    • v.10 no.5
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    • pp.95-102
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    • 2019
  • This study was to investigate the effect of eye movement and intentional finger movement on cognitive ability. Normal adult subjects were randomly divided into two groups: saccadic eye movement(SEM) and intentional finger movement(IFM). After 2 weeks of intervention, Digit span was used for short-term memory test and N-back was used for working memory test. As a result, the short-term memory of the IFM group increased significantly over time, and the follow-up test showed difference between group. The IFM group's the execution time, the error count and the accuracy rate of n-back item showed significant effects over time. The SEM group's the execution time and the accuracy of n-back item showed significant effects over time. In conclusion, the IFM method, which is a multiple stimulus that can activate the cerebral cortex more extensively than the single stimulus SEM, may be more useful as an intervention method of cognitive function improvement.

A Study on the Image Based Auto-focus Method Considering Jittering of Airborne EO/IR (항공탑재 EO/IR의 영상떨림을 고려한 영상기반 자동 초점조절 기법 연구)

  • Kang, Myung-Ho;Kim, Sung-Jae;Koh, Yeong Jun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.1
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    • pp.39-45
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    • 2022
  • In this paper, we propose methods to improve image-based auto-focus that can compensate for drawbacks of traditional auto-focus control. When adjusting the focus, there is a problem that the focus window cannot be set to the same position if the camera's LOS is not directed at the same location and flow or shake. To address this issue, we applied image tracking techniques to improve optimal focus localization accuracy. And also, although the same focus value should be calculated at the same focus step, but different values can be calculated by camera's fine shaking or image disturbance due to atmospheric scattering. To tackle this problem a SAFS (Stable Adjacency Frame Selection) has been proposed. As a result of this study, our proposed methodology shows more accurate than traditional methods in terms of finding best focus position.

An accuracy analysis of Cyberknife tumor tracking radiotherapy according to unpredictable change of respiration (예측 불가능한 호흡 변화에 따른 사이버나이프 종양 추적 방사선 치료의 정확도 분석)

  • Seo, jung min;Lee, chang yeol;Huh, hyun do;Kim, wan sun
    • The Journal of Korean Society for Radiation Therapy
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    • v.27 no.2
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    • pp.157-166
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    • 2015
  • Purpose : Cyber-Knife tumor tracking system, based on the correlation relationship between the position of a tumor which moves in response to the real time respiratory cycle signal and respiration was obtained by the LED marker attached to the outside of the patient, the location of the tumor to predict in advance, the movement of the tumor in synchronization with the therapeutic device to track real-time tumor, is a system for treating. The purpose of this study, in the cyber knife tumor tracking radiation therapy, trying to evaluate the accuracy of tumor tracking radiation therapy system due to the change in the form of unpredictable sudden breathing due to cough and sleep. Materials and Methods : Breathing Log files that were used in the study, based on the Respiratory gating radiotherapy and Cyber-knife tracking radiosurgery breathing Log files of patients who received herein, measured using the Log files in the form of a Sinusoidal pattern and Sudden change pattern. it has been reconstituted as possible. Enter the reconstructed respiratory Log file cyber knife dynamic chest Phantom, so that it is possible to implement a motion due to respiration, add manufacturing the driving apparatus of the existing dynamic chest Phantom, Phantom the form of respiration we have developed a program that can be applied to. Movement of the phantom inside the target (Ball cube target) was driven by the displacement of three sizes of according to the size of the respiratory vertical (Superior-Inferior) direction to the 5 mm, 10 mm, 20 mm. Insert crosses two EBT3 films in phantom inside the target in response to changes in the target movement, the End-to-End (E2E) test provided in Cyber-Knife manufacturer depending on the form of the breathing five times each. It was determined by carrying. Accuracy of tumor tracking system is indicated by the target error by analyzing the inserted film, additional E2E test is analyzed by measuring the correlation error while being advanced. Results : If the target error is a sine curve breathing form, the size of the target of the movement is in response to the 5 mm, 10 mm, 20 mm, respectively, of the average $1.14{\pm}0.13mm$, $1.05{\pm}0.20mm$, with $2.37{\pm}0.17mm$, suddenly for it is variations in breathing, respective average $1.87{\pm}0.19mm$, $2.15{\pm}0.21mm$, and analyzed with $2.44{\pm}0.26mm$. If the correlation error can be defined by the length of the displacement vector in the target track is a sinusoidal breathing mode, the size of the target of the movement in response to 5 mm, 10 mm, 20 mm, respective average $0.84{\pm}0.01mm$, $0.70{\pm}0.13mm$, with $1.63{\pm}0.10mm$, if it is a variant of sudden breathing respective average $0.97{\pm}0.06mm$, $1.44{\pm}0.11mm$, and analyzed with $1.98{\pm}0.10mm$. The larger the correlation error values in both the both the respiratory form, the target error value is large. If the motion size of the target of the sine curve breathing form is greater than or equal to 20 mm, was measured at 1.5 mm or more is a recommendation value of both cyber knife manufacturer of both error value. Conclusion : There is a tendency that the correlation error value between about target error value magnitude of the target motion is large is increased, the error value becomes large in variation of rapid respiration than breathing the form of a sine curve. The more the shape of the breathing large movements regular shape of sine curves target accuracy of the tumor tracking system can be judged to be reduced. Using the algorithm of Cyber-Knife tumor tracking system, when there is a change in the sudden unpredictable respiratory due patient coughing during treatment enforcement is to stop the treatment, it is assumed to carry out the internal target validation process again, it is necessary to readjust the form of respiration. Patients under treatment is determined to be able to improve the treatment of accuracy to induce the observed form of regular breathing and put like to see the goggles monitor capable of the respiratory form of the person.

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An Energy-efficient Edge Detection Method for Continuous Object Tracking in Wireless Sensor Networks (무선 센서 네트워크에서의 연속적인 물체의 추적을 위한 에너지 효율적인 경계 선정 기법)

  • Jang, Sang-Wook;Hahn, Joo-Sun;Ha, Rhan
    • Journal of KIISE:Information Networking
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    • v.36 no.6
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    • pp.514-527
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    • 2009
  • Wireless sensor networks (WSNs) can be used in various applications for military or environmental purpose. Recently, there are lots of on-going researches for detecting and tracking the spread of continuous objects or phenomena such as poisonous gas, wildfires, earthquakes, and so on. Some previous work has proposed techniques to detect edge nodes of such a continuous object based on the information of all the 1-hop neighbor nodes. In those techniques, however, a number of nodes are redundantly selected as edge nodes, and thus, the boundary of the continuous object cannot be presented accurately. In this paper, we propose a new edge detection method in which edge nodes of the continuous object are detected based on the information of the neighbor nodes obtained via the Localized Delaunay Triangulation so that a minimum number of nodes are selected as edge nodes. We also define the sensor behavior rule for tracking continuous objects energy-efficiently. Our simulation results show that the proposed edge detection method provides enhanced performance compared with previous 1-hop neighbor node based methods. On the average, the accuracy is improved by 29.95% while the number of edge nodes, the amount of communication messages and energy consumption are reduced by 54.43%, 79.36% and 72.34%, respectively. Moreover, the number of edge nodes decreases by 48.38% on the average in our field test with MICAz motes.

The efficient IR-UWB Radar System for Reflective Wave Removal in a Short Distance Environments (근거리 환경에서 반사파 제거를 위한 효율적인 IR-UWB Radar 시스템)

  • Kim, Sueng-Woo;Jeong, Won-Ho;Yeo, Bong-Gu;Kim, Kyung-Seok
    • Journal of Satellite, Information and Communications
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    • v.12 no.1
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    • pp.64-71
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    • 2017
  • In this paper, Kalman filter and RRWA algorithm are used to estimate the accurate target in IR-UWB (Impulse-Radio Ultra Wideband) radar system, which enables accurate location recognition of indoors and outdoors with low cost and low power consumption. In the signal reflected by the target, unnecessary signals exist in addition to the target signal. We have tried to remove unnecessary signals and to derive accurate target signals and improve performance. The location of the targets is estimated in real time with one transmitting antenna and one receiving antenna. The Kalman filter was used to remove the background noise and the RRWA algorithm was used to remove the reflected signal. In this paper, we think that it will be useful to study the accurate distance estimation and tracking in future target estimation.

Research on Human Posture Recognition System Based on The Object Detection Dataset (객체 감지 데이터 셋 기반 인체 자세 인식시스템 연구)

  • Liu, Yan;Li, Lai-Cun;Lu, Jing-Xuan;Xu, Meng;Jeong, Yang-Kwon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.1
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    • pp.111-118
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    • 2022
  • In computer vision research, the two-dimensional human pose is a very extensive research direction, especially in pose tracking and behavior recognition, which has very important research significance. The acquisition of human pose targets, which is essentially the study of how to accurately identify human targets from pictures, is of great research significance and has been a hot research topic of great interest in recent years. Human pose recognition is used in artificial intelligence on the one hand and in daily life on the other. The excellent effect of pose recognition is mainly determined by the success rate and the accuracy of the recognition process, so it reflects the importance of human pose recognition in terms of recognition rate. In this human body gesture recognition, the human body is divided into 17 key points for labeling. Not only that but also the key points are segmented to ensure the accuracy of the labeling information. In the recognition design, use the comprehensive data set MS COCO for deep learning to design a neural network model to train a large number of samples, from simple step-by-step to efficient training, so that a good accuracy rate can be obtained.