• Title/Summary/Keyword: Camera sensor

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Camera Identification of DIBR-based Stereoscopic Image using Sensor Pattern Noise (센서패턴잡음을 이용한 DIBR 기반 입체영상의 카메라 판별)

  • Lee, Jun-Hee
    • Journal of the Korea Institute of Military Science and Technology
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    • v.19 no.1
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    • pp.66-75
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    • 2016
  • Stereoscopic image generated by depth image-based rendering(DIBR) for surveillance robot and camera is appropriate in a low bandwidth network. The image is very important data for the decision-making of a commander and thus its integrity has to be guaranteed. One of the methods used to detect manipulation is to check if the stereoscopic image is taken from the original camera. Sensor pattern noise(SPN) used widely for camera identification cannot be directly applied to a stereoscopic image due to the stereo warping in DIBR. To solve this problem, we find out a shifted object in the stereoscopic image and relocate the object to its orignal location in the center image. Then the similarity between SPNs extracted from the stereoscopic image and the original camera is measured only for the object area. Thus we can determine the source of the camera that was used.

Camera and LiDAR Sensor Fusion for Improving Object Detection (카메라와 라이다의 객체 검출 성능 향상을 위한 Sensor Fusion)

  • Lee, Jongseo;Kim, Mangyu;Kim, Hakil
    • Journal of Broadcast Engineering
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    • v.24 no.4
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    • pp.580-591
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    • 2019
  • This paper focuses on to improving object detection performance using the camera and LiDAR on autonomous vehicle platforms by fusing detected objects from individual sensors through a late fusion approach. In the case of object detection using camera sensor, YOLOv3 model was employed as a one-stage detection process. Furthermore, the distance estimation of the detected objects is based on the formulations of Perspective matrix. On the other hand, the object detection using LiDAR is based on K-means clustering method. The camera and LiDAR calibration was carried out by PnP-Ransac in order to calculate the rotation and translation matrix between two sensors. For Sensor fusion, intersection over union(IoU) on the image plane with respective to the distance and angle on world coordinate were estimated. Additionally, all the three attributes i.e; IoU, distance and angle were fused using logistic regression. The performance evaluation in the sensor fusion scenario has shown an effective 5% improvement in object detection performance compared to the usage of single sensor.

Developing a CIS Camera Interface for Embedded Systems (임베디드 시스템에서 CIS 카메라 인터페이스의 구현)

  • Lee, Wan-Su;Oh, Sam-Kwan;Hwang, Hee-Yeung;Roh, Young-Sub
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.8 no.3
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    • pp.513-521
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    • 2007
  • Recently, camera function is one of the most primary functions out of the multimedia capabilities in the small mobile terminals. But, it has been difficult for implementing embedded devices with low cost because of not supporting camera interface in many SoCs. Thus, this paper presents a method of supporting camera function with ease for embedded devices which has not camera interface. For this purpose, the interface is implemented for a CMOS image sensor. The method is also provided that CIS(CMOS Image Sensor) is supported in the embedded system by programming the device driver.

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Virtual Environment Building and Navigation of Mobile Robot using Command Fusion and Fuzzy Inference

  • Jin, Taeseok
    • Journal of the Korean Society of Industry Convergence
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    • v.22 no.4
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    • pp.427-433
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    • 2019
  • This paper propose a fuzzy inference model for map building and navigation for a mobile robot with an active camera, which is intelligently navigating to the goal location in unknown environments using sensor fusion, based on situational command using an active camera sensor. Active cameras provide a mobile robot with the capability to estimate and track feature images over a hallway field of view. In this paper, instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. Command fusion method is used to govern the robot navigation. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of active camera sensor for navigation experiments are fused into the identification process. Navigation performance improves on that achieved using fuzzy inference alone and shows significant advantages over command fusion techniques. Experimental evidences are provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the active camera and the feature images.

An Intelligent Wireless Camera Surveillance System with Motion sensor and Remote Control (무선조종과 모션 센서를 이용한 지능형 무선감시카메라 구현)

  • Lee, Young-Woong;Kim, Jong-Nam
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.672-676
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    • 2009
  • Recently, intelligent surveillance camera systems are needed popularly. However, current researches are focussed on improvement of a single module rather than implementation of an integrated system. In this paper, we implemented a wireless surveillance camera system which is composed of face detection, and using motion sensor. In our implementation, we used a camera module from SHARP, a pair of wireless video transmission module from ECOM, a pair of ZigBee RF wireless transmission module from ROBOBLOCK, and a motion sensor module (AMN14111) from PANASONIC. We used OpenCV library for face dection and MFC for implement software. We identified real-time operations of face detection, PTT control, and motion sensor detecton. Thus, the implemented system will be useful for the applications of remote control, human detection, and using motion sensor.

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Improvement of Multiple-sensor based Frost Observation System (MFOS v2) (다중센서 기반 서리관측 시스템의 개선: MFOS v2)

  • Suhyun Kim;Seung-Jae Lee;Kyu Rang Kim
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.3
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    • pp.226-235
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    • 2023
  • This study aimed to supplement the shortcomings of the Multiple-sensor-based Frost Observation System (MFOS). The developed frost observation system is an improvement of the existing system. Based on the leaf wetness sensor (LWS), it not only detects frost but also functions to predict surface temperature, which is a major factor in frost occurrence. With the existing observation system, 1) it is difficult to observe ice (frost) formation on the surface when capturing an image of the LWS with an RGB camera because the surface of the sensor reflects most visible light, 2) images captured using the RGB camera before and after sunrise are dark, and 3) the thermal infrared camera only shows the relative high and low temperature. To identify the ice (frost) generated on the surface of the LWS, a LWS that was painted black and three sheets of glass at the same height to be used as an auxiliary tool to check the occurrence of ice (frost) were installed. For RGB camera shooting before and after sunrise, synchronous LED lighting was installed so the power turns on/off according to the camera shooting time. The existing thermal infrared camera, which could only assess the relative temperature (high or low), was improved to extract the temperature value per pixel, and a comparison with the surface temperature sensor installed by the National Institute of Meteorological Sciences (NIMS) was performed to verify its accuracy. As a result of installing and operating the MFOS v2, which reflects these improvements, the accuracy and efficiency of automatic frost observation were demonstrated to be improved, and the usefulness of the data as input data for the frost prediction model was enhanced.

A Study on Portable Green-algae Remover Device based on Arduino and OpenCV using Do Sensor and Raspberry Pi Camera (DO 센서와 라즈베리파이 카메라를 활용한 아두이노와 OpenCV기반의 이동식 녹조제거장치에 관한 연구)

  • Kim, Min-Seop;Kim, Ye-Ji;Im, Ye-Eun;Hwang, You-Seong;Baek, Soo-Whang
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.4
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    • pp.679-686
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    • 2022
  • In this paper, we implemented an algae removal device that recognizes and removes algae existing in water using Raspberry Pi camera and DO (Dissolved Oxygen) sensor. The Raspberry Pi board recognizes the color of green algae by converting the RGB values obtained from the camera into HSV. Through this, the location of the algae is identified and when the amount of dissolved oxygen's decrease at the location is more than the reference value using the DO sensor, the algae removal device is driven to spray the algae removal solution. Raspberry Pi's camera uses OpenCV, and the motor movement is controlled according to the output value of the DO sensor and the result of the camera's green algae recognition. Algae recognition and spraying of algae removal solution were implemented through Arduino and Raspberry Pi, and the feasibility of the proposed portable algae removal device was verified through experiments.

Compressed Sensing-based Multiple-target Tracking Algorithm for Ad Hoc Camera Sensor Networks

  • Lu, Xu;Cheng, Lianglun;Liu, Jun;Chen, Rongjun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1287-1300
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    • 2018
  • Target-tracking algorithm based on ad hoc camera sensor networks (ACSNs) utilizes the distributed observation capability of nodes to achieve accurate target tracking. A compressed sensing-based multiple-target tracking algorithm (CSMTTA) for ACSNs is proposed in this work based on the study of camera node observation projection model and compressed sensing model. The proposed algorithm includes reconfiguration of observed signals and evaluation of target locations. It reconfigures observed signals by solving the convex optimization of L1-norm least and forecasts node group to evaluate a target location by the motion features of the target. Simulation results show that CSMTTA can recover the subtracted observation information accurately under the condition of sparse sampling to a high target-tracking accuracy and accomplish the distributed tracking task of multiple mobile targets.

A Study on Intelligent Robot Bin-Picking System with CCD Camera and Laser Sensor (CCD카메라와 레이저 센서를 조합한 지능형 로봇 빈-피킹에 관한 연구)

  • Shin, Chan-Bai;Kim, Jin-Dae;Lee, Jeh-Won
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.231-233
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    • 2007
  • In this paper we present a new visual approach for the robust bin-picking in a two-step concept for a vision driven automatic handling robot. The technology described here is based on two types of sensors: 3D laser scanner and CCD video camera. The geometry and pose(position and orientation) information of bin contents was reconstructed from the camera and laser sensor. these information can be employed to guide the robotic arm. A new thinning algorithm and constrained hough transform method is also explained in this paper. Consequently, the developed bin-picking demonstrate the successful operation with 3D hole object.

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ANALYSIS OF THE IMAGE SENSOR CONTROL METHOD

  • Park, Jong-Euk;Kong, Jong-Pil;Heo, Haeng-Pal;Kim, Young-Sun;Yong, Sang-Soon
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.464-467
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    • 2007
  • All image data acquisition systems for example the digital camera and digital camcorder, use the image sensor to convert the image data (light) into electronic data. These image sensors are used in satellite camera for high quality and resolution image data. There are two kinds of image sensors, the one is the CCD (charge coupled device) detector sensor and the other is the CMOS (complementary metal-oxide semiconductor) image sensor. The CCD sensor control system has more complex than the CMOS sensor control system. For the high quality image data on CCD sensor, the precise timing control signal and the several voltage sources are needed in the control system. In this paper, the comparison of the CCD with CMOS sensor, the CCD sensor characteristic, and the control system will be described.

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