• Title/Summary/Keyword: Detecting Area

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A Comparative Study for Red Tide Detection Methods Using GOCI and MODIS

  • Oh, Seung-Yeol;Jang, Seon-Woong;Park, Won-Gyu;Lee, Jun-Ho;Yoon, Hong-Joo
    • Korean Journal of Remote Sensing
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    • v.29 no.3
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    • pp.331-335
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    • 2013
  • This study detected red tide areas using the existing Moderate-Resolution Imaging Spectroradiometer(MODIS) and Geostationary Ocean Color Imager(GOCI), and then compared the results between results of two sensors. The coasts of Jeollanam-do in the South Sea of Korea were set as the study area based on the red tide data which occurred on Aug. 26th, 2012. This study compared the results of sensors to detect red tides by using a satellite. In the results of analyzing MODIS by limiting it as chlorophyll concentration and the sea surface temperature which is considered to have red tides by the existing researches, it was possible to delete considerable amount of errors compared to the case of detecting red tides by using only chlorophyll while still there were differences from the range of red tides actually observed. In the results of GOCI by using empirical algorithm for detecting red tides, currently used by Korea Institute of Ocean Science & Technology(KIOST), it was possible to obtain more detailed results than MODIS. However, there was an area misjudged as red tides due to the influence of clouds. Also both MODIS and GOCI extracted red tides were not actually occurring, which might be because they were not able to perfectly distinguish red tides from turbid water in coastal areas with high turbidity.

A Chip Design of Body Composition Analyzer (체성분 분석용 칩 설계)

  • Bae, Sung-Hoon;Moon, Byoung-Sam;Lim, Shin-Il
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.44 no.3 s.357
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    • pp.26-34
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    • 2007
  • This Paper describes a chip design technique for body composition analyzer based on the BIA (Bioelectrical Impedance Analysis) method. All the functions of signal forcing circuits to the body, signal detecting circuits from the body, Micom, SRAM and EEPROMS are integrated in one chip. Especially, multi-frequency detecting method can be applied with selective band pass filter (BPF), which is designed in weak inversion region for low power consumption. In addition new full wave rectifier (FWR) is also proposed with differential difference amplifier (DDA) for high performance (small die area low power consumption, rail-to-rail output swing). The prototype chip is implemented with 0.35um CMOS technology and shows the power dissipation of 6 mW at the supply voltage of 3.3V. The die area of prototype chip is $5mm\times5mm$.

A method of generating virtual shadow dataset of buildings for the shadow detection and removal

  • Kim, Kangjik;Chun, Junchul
    • Journal of Internet Computing and Services
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    • v.21 no.5
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    • pp.49-56
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    • 2020
  • Detecting shadows in images and restoring or removing them was a very challenging task in computer vision. Traditional researches used color information, edges, and thresholds to detect shadows, but there were errors such as not considering the penumbra area of shadow or even detecting a black area that is not a shadow. Deep learning has been successful in various fields of computer vision, and research on applying deep learning has started in the field of shadow detection and removal. However, it was very difficult and time-consuming to collect data for network learning, and there were many limited conditions for shooting. In particular, it was more difficult to obtain shadow data from buildings and satellite images, which hindered the progress of the research. In this paper, we propose a method for generating shadow data from buildings and satellites using Unity3D. In the virtual Unity space, 3D objects existing in the real world were placed, and shadows were generated using lights effects to shoot. Through this, it is possible to get all three types of images (shadow-free, shadow image, shadow mask) necessary for shadow detection and removal when training deep learning networks. The method proposed in this paper contributes to helping the progress of the research by providing big data in the field of building or satellite shadow detection and removal research, which is difficult for learning deep learning networks due to the absence of data. And this can be a suboptimal method. We believe that we have contributed in that we can apply virtual data to test deep learning networks before applying real data.

Detecting Land Cover Change in an Urban Area by Image Differencing and Image Ratioing Techniques (영상의 차연산과 비연산 기법에 의한 도시지역의 토지피복 변화탐지)

  • Lee, Jin-Duk;Jo, Chang-Hwan
    • Journal of Korean Society for Geospatial Information Science
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    • v.12 no.2 s.29
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    • pp.43-52
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    • 2004
  • This study presents the application of aerial photographs and the Korea Multi-Purpose Satellite, KOMPSAT-1 Electro-Optical Camera(EOC) imagery in detecting change in an urban area that has been rapidly growing. For the study, we used multi-temporal images which were acquired by two different sensors. Image registration and resampling were rallied out before performing change detection in a common reference system with the same spatial resolution. for all of the images. Results from image differencing and image ratioing techniques show that panchromatic aerial photographs and KOMPSAT-1 EOC images collected by different sensors have potential to detect changes of urban features such as building, road and other man-made structure. And the optimal threshold values were suggested in applying image differencing and image ratioing techniques for change detection.

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Real-Time Traffic Information Collection Using Multiple Virtual Detection Lines (다중 가상 검지선을 이용한 실시간 교통정보 수집)

  • Kim, Eui-Chul;Kim, Soo-Hyung;Lee, Guee-Sang;Yang, Hyung-Jeong
    • The KIPS Transactions:PartB
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    • v.15B no.6
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    • pp.543-552
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    • 2008
  • ATIS(Advanced Traveler Information System) is the system to offer a real-time traffic information or traffic situation for the benefit of the client. One of traffic information collection methods for ATIS research is the method of image analysis. The method is divided into two : one is the method to set two loop detectors at the area and the other is the method detecting the vehicle through an image analysis. In this paper, we propose a real-time traffic information collection system to mix two methods. The system installs multiple virtual detection lines and traces the location of the vehicle. Use of multiple virtual detection lines supplements the defect of the method of loop detectors. And we drew a representative pixels in the detecting area and used it for image analysis. This is to solve the problem of time delay which increases as the image size increases. We gathered traffic images and experimented using the system and got 92.32% of detection accuracy.

Endpoint Detection Using Hybrid Algorithm of PLS and SVM (PLS와 SVM복합 알고리즘을 이용한 식각 종료점 검출)

  • Lee, Yun-Keun;Han, Yi-Seul;Hong, Sang-Jeen;Han, Seung-Soo
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.24 no.9
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    • pp.701-709
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    • 2011
  • In semiconductor wafer fabrication, etching is one of the most critical processes, by which a material layer is selectively removed. Because of difficulty to correct a mistake caused by over etching, it is critical that etch should be performed correctly. This paper proposes a new approach for etch endpoint detection of small open area wafers. The traditional endpoint detection technique uses a few manually selected wavelengths, which are adequate for large open areas. As the integrated circuit devices continue to shrink in geometry and increase in device density, detecting the endpoint for small open areas presents a serious challenge to process engineers. In this work, a high-resolution optical emission spectroscopy (OES) sensor is used to provide the necessary sensitivity for detecting subtle endpoint signal. Partial Least Squares (PLS) method is used to analyze the OES data which reduces dimension of the data and increases gap between classes. Support Vector Machine (SVM) is employed to detect endpoint using the data after PLS. SVM classifies normal etching state and after endpoint state. Two data sets from OES are used in training PLS and SVM. The other data sets are used to test the performance of the model. The results show that the trained PLS and SVM hybrid algorithm model detects endpoint accurately.

Computer Vision-based Method of detecting a Approaching Vehicle or the Safety of a Bus Passenger Getting off (버스 승객의 안전한 하차를 위한 컴퓨터비전 기반의 차량 탐지 시스템 개발)

  • Lee Kwang-Soon;Lee Kyung-Bok;Rho Kwang-Hyun;Han Min-Hong
    • Journal of the Institute of Convergence Signal Processing
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    • v.6 no.1
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    • pp.1-7
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    • 2005
  • This paper describes the system for detecting vehicles in the rear and rear-side that access between sidewalk and bus stopped to city road at day by computer vision-based method. This system informs appearance of vehicles to bus driver and passenger for the safety of a bus passenger getting off. The camera mounted on the top portion of the bus exit door gets the rear and rear-side image of the bus whenever a bus stops at the stop. The system sets search area between bus and sidewalk from this image and detects a vehicle by using change of image and sobel filtering in this area. From a central point of the vehicle detected, we can find out the distance, speed and direction by its location, width and length. It alarms the driver and passengers when it's judged that dangerous situation for the passenger getting off happens. This experiment results in a detection rate more than 87% in driving by bus on the road.

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A Study on the Practice of Engineering Education through the Design and Production of Drones for Detecting Objects in Disaster Area (재난 지역의 물체를 탐지하기 위한 소형 무인기 설계와 제작을 통한 공학 교육의 실천에 관한 연구)

  • Kang, Byeong-Ju;Lee, Dae-Hee;Chang, Eun-Young
    • Journal of Practical Engineering Education
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    • v.9 no.1
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    • pp.15-21
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    • 2017
  • In order to satisfy the graduation requirements, the graduation work should be presented as an engineering dissertation system of the produced work and an outline of the procedure made by the major unit in accordance with the graduation thesis submission rules, and suggests necessary matters for improvement. The design content relates to a small unmanned aerial vehicle configuration for detecting personnel or objects in a disaster area. It is equipped with an infrared sensor and a GPS in the drone, the drone is control by using Blutooth communications. The drones detect the target and use the GPS to determine the location. As a result of the experiment, it was possible to detect the structure object within the range of 3~4 m, confirm the transmission of the position value in real time, and increase the communication distance by using RF communication.

Determination of Bar Code Cross-line Based on Block HOG Clustering (블록 HOG 군집화 기반의 1-D 바코드 크로스라인 결정)

  • Kim, Dong Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.7
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    • pp.996-1003
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    • 2022
  • In this paper, we present a new method for determining the scan line and range for vision-based 1-D barcode recognition. This is a study on how to detect valid barcode representative points and directions by applying the DBSCAN clustering method based on block HOG (histogram of gradient) and determine scan lines and barcode crosslines based on this. In this paper, the minimum and maximum search techniques were applied to determine the cross-line range of barcodes based on the obtained scan lines. This can be applied regardless of the barcode size. This technique enables barcode recognition even by detecting only a partial area of the barcode, and does not require rotation to read the code after detecting the barcode area. In addition, it is possible to detect barcodes of various sizes. Various experimental results are presented to evaluate the performance of the proposed technique in this paper.

Development of the Blind Spot Detecting System for Vehicle (차량용 사각지대 감지시스템의 개발)

  • Yoon, Moon-Young;Kim, Se-Hun;Son, Min-Hyuk;Yun, Duk-Sun;Boo, Kwang-Seok;Kim, Heung-Seob
    • Transactions of the Korean Society of Automotive Engineers
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    • v.17 no.2
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    • pp.34-41
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    • 2009
  • The latest vehicle yields a superior safety and reduction of driving burden by monitoring the driving state of vehicle and its environment with various sensors. To detect other vehicles and objects of the rear left and right-side blind spot area of driver, provide the information about a existence of objects inside the blind spot, and give a signal to avoid collision, this study proposes the intelligent outside rear-view mirror system. This task has substantially complicated several factors. For example, the size, geometry and features of the various vehicles which might enter the monitored zone is varied widely and therefore present various reflective characteristics. This study proposes the optimal specification and configuration of optical system and IR array sensor of blind spot detection system, and shows the results of the performance evaluation of developed system.