• Title/Summary/Keyword: camera image

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Water Level Tracking System based on Morphology and Template Matching

  • Ansari, Israfil;Jeong, Yunju;Lee, Yeunghak;Shim, Jaechang
    • Journal of Korea Multimedia Society
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    • v.21 no.12
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    • pp.1431-1438
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    • 2018
  • In this paper, we proposed a river water level detection and tracking of the river or dams based on image processing system. In past, most of the water level detection system used various water sensors. Those water sensors works perfectly but have many drawbacks such as high cost and harsh weather. Water level monitoring system helps in forecasting early river disasters and maintenance of the water body area. However, the early river disaster warning system introduces many conflicting requirements. Surveillance camera based water level detection system depends on either the area of interest from the water body or on optical flow algorithm. This proposed system is focused on water scaling area of a river or dam to detect water level. After the detection of scale area from water body, the proposed algorithm will immediately focus on the digits available on that area. Using the numbers on the scale, water level of the river is predicted. This proposed system is successfully tested on different water bodies to detect the water level area and predicted the water level.

Characteristics of Infrared Blocking, Stealth and Color Difference of Aluminum Sputtered Fabrics

  • Han, Hye Ree
    • Journal of the Korean Society of Clothing and Textiles
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    • v.43 no.4
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    • pp.592-604
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    • 2019
  • This study examines the stealth function of sputtered fabric with an infrared thermal imaging camera in terms of the thermal and infrared (IR) transmittance characteristics. Various base fabrics were selected, infrared imaging was performed, and infrared transmittance was measured. By infrared camera experiment it was found that the sample was concealed because it had a similar color to the surroundings when the aluminum layer was directed toward the outside. In addition, a comparison of the infrared thermographic image of the untreated sample and the sputtered sample in the laboratory showed that the difference in ${\Delta}E$ value ranged from 31 to 90.4 and demonstrated effective concealment. However, concealment was not observed in the case of the 3-layer (Nylon-Al-Nylon) model when a sputtered aluminum layer existed between two nylon layers. The direction of the sputtering layer did not affect the infrared transmittance in the infrared transmittance experiment. Therefore, it seems better to interpret the concealing effect in the infrared thermographic images by using thermal transfer theory rather than infrared transmittance theory. We believe that the results of this study will be applicable to developing high performance smart clothing and military uniforms.

High Accuracy Skeleton Estimation using 3D Volumetric Model based on RGB-D

  • Kim, Kyung-Jin;Park, Byung-Seo;Kang, Ji-Won;Kim, Jin-Kyum;Kim, Woo-Suk;Kim, Dong-Wook;Seo, Young-Ho
    • Journal of Broadcast Engineering
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    • v.25 no.7
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    • pp.1095-1106
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    • 2020
  • In this paper, we propose an algorithm that extracts a high-precision 3D skeleton using a model generated using a distributed RGB-D camera. When information about a 3D model is extracted through a distributed RGB-D camera, if the information of the 3D model is used, a skeleton with higher precision can be obtained. In this paper, in order to improve the precision of the 2D skeleton, we find the conditions to obtain the 2D skeleton well using the PCA. Through this, high-quality 2D skeletons are obtained, and high-precision 3D skeletons are extracted by combining the information of the 2D skeletons. Even though this process goes through, the generated skeleton may have errors, so we propose an algorithm that removes these errors by using the information of the 3D model. We were able to extract very high accuracy skeletons using the proposed method.

HearCAM Embedded Platform Design (히어 캠 임베디드 플랫폼 설계)

  • Hong, Seon Hack;Cho, Kyung Soon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.10 no.4
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    • pp.79-87
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    • 2014
  • In this paper, we implemented the HearCAM platform with Raspberry PI B+ model which is an open source platform. Raspberry PI B+ model consists of dual step-down (buck) power supply with polarity protection circuit and hot-swap protection, Broadcom SoC BCM2835 running at 700MHz, 512MB RAM solered on top of the Broadcom chip, and PI camera serial connector. In this paper, we used the Google speech recognition engine for recognizing the voice characteristics, and implemented the pattern matching with OpenCV software, and extended the functionality of speech ability with SVOX TTS(Text-to-speech) as the matching result talking to the microphone of users. And therefore we implemented the functions of the HearCAM for identifying the voice and pattern characteristics of target image scanning with PI camera with gathering the temperature sensor data under IoT environment. we implemented the speech recognition, pattern matching, and temperature sensor data logging with Wi-Fi wireless communication. And then we directly designed and made the shape of HearCAM with 3D printing technology.

Design of Turbidity Measurement of White Plume using Optical Method (광학기법을 이용한 백색 굴뚝연기 혼탁도 측정의 설계)

  • Son, Hyun-Keun;Ban, Chae-Hoon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.6
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    • pp.1195-1200
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    • 2020
  • The DOM (: Digital Optical Method), which measures the turbidity of chimney smoke, is a method of calculating the turbidity by setting the area to be measured and the contrast area using a low-cost digital camera that can be easily obtained. However, it is difficult to measure clouds and white smoke in a cloudy sky. In this paper, we develop a background sky type model that can represent the background sky and classify the type by periodically photographing it with a digital camera to solve this problem. In addition, based on the model, we develop a filter to optimize white smoke image and prove its excellence through experiments.

A study on the detection of pedestrians in crosswalks using multi-spectrum (다중스펙트럼을 이용한 횡단보도 보행자 검지에 관한 연구)

  • kim, Junghun;Choi, Doo-Hyun;Lee, JongSun;Lee, Donghwa
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.1
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    • pp.11-18
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    • 2022
  • The use of multi-spectral cameras is essential for day and night pedestrian detection. In this paper, a color camera and a thermal imaging infrared camera were used to detect pedestrians near a crosswalk for 24 hours at an intersection with a high risk of traffic accidents. For pedestrian detection, the YOLOv5 object detector was used, and the detection performance was improved by using color images and thermal images at the same time. The proposed system showed a high performance of 0.940 mAP in the day/night multi-spectral (color and thermal image) pedestrian dataset obtained from the actual crosswalk site.

Optical Design of a Snapshot Nonmydriatic Fundus-imaging Spectrometer Based on the Eye Model

  • Zhao, Xuehui;Chang, Jun;Zhang, Wenchao;Wang, Dajiang;Chen, Weilin;Cao, Jiajing
    • Current Optics and Photonics
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    • v.6 no.2
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    • pp.151-160
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    • 2022
  • Fundus images can reflect ocular diseases and systemic diseases such as glaucoma, diabetes mellitus, and hypertension. Thus, research on fundus-detection equipment is of great importance. The fundus camera has been widely used as a kind of noninvasive detection equipment. Most existing devices can only obtain two-dimensional (2D) retinal-image information, yet the fundus of the human eye also has spectral characteristics. The fundus has many pigments, and their different distributions in the eye lead to dissimilar tissue penetration for light waves, which can reflect the corresponding fundus structure. To obtain more abundant information and improve the detection level of equipment, a snapshot nonmydriatic fundus imaging spectral system, including fundus-imaging spectrometer and illumination system, is studied in this paper. The system uses a microlens array to realize snapshot technology; information can be obtained from only a single exposure. The system does not need to dilate the pupil. Hence, the operation is simple, which reduces its influence on the detected object. The system works in the visible and near-infrared bands (550-800 nm), with a volume less than 400 mm × 120 mm × 75 mm and a spectral resolution better than 6 nm.

Smart Streetlight based on Accident Recognition using Raspberry Pi Camera OpenCV (라즈베리파이 카메라 OpenCV를 활용한 사고 인식 기반 스마트 가로등)

  • Dong-Jin, Kim;Won-Seok, Choi;Sung-Pyo, Ju;Seung-Min, Yoo;Jae-Yong, Choi;Hyoung-Keun, Park
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.6
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    • pp.1229-1236
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    • 2022
  • In this paper, we studied accident-aware smart streetlights to prevent secondary accidents when driving on highways. It used Arduino and sensors to inform drivers of weather conditions, incorporated functions such as LED brightness control according to sunlight and night driving vehicles, and used Raspberry Pi camera OpenCV to learn various traffic accidents, natural disasters, and wildlife.

A Multi-Sensor Module of Snake Robot for Searching Survivors in Narrow Space (협소 공간 생존자 탐색을 위한 뱀형 로봇의 다중 센서 모듈)

  • Kim, Sungjae;Shin, Dong-Gwan;Pyo, Juhyun;Shin, Juseong;Jin, Maolin;Suh, Jinho
    • The Journal of Korea Robotics Society
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    • v.16 no.4
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    • pp.291-298
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    • 2021
  • In this study, we present a multi-sensor module for snake robot searching survivors in a narrow space. To this end, we integrated five sensor systems by considering the opinions of the first responders: a gas sensor to detect CO2 gases from the exhalation of survivors, a CMOS camera to provide the image of survivors, an IR camera to see in the dark & smoky environment, two microphones to detect the voice of survivors, and an IMU to recognize the approximate location and direction of the robot and survivors. Furthermore, we integrated a speaker into the sensor module system to provide a communication channel between the first responders and survivors. To integrated all these mechatronics systems in a small, compact snake head, we optimized the positions of the sensors and designed a stacked structure for the whole system. We also developed a user-friendly GUI to show the information from the proposed sensor systems visually. Experimental results verified the searching function of the proposed sensor module system.

Development of Color Recognition Algorithm for Traffic Lights using Deep Learning Data (딥러닝 데이터 활용한 신호등 색 인식 알고리즘 개발)

  • Baek, Seoha;Kim, Jongho;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.2
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    • pp.45-50
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    • 2022
  • The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios.