• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.54-61
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• 2012

In this paper, the pose estimation method for the satellite GTB (Ground Test Bed) using vision/MEMS IMU (Inertial Measurement Unit) integrated system is presented. The GTB for verifying a satellite system on the ground is similar to the mobile robot having thrusters and a reaction wheel as actuators and floating on the floor by compressed air. The EKF (Extended Kalman Filter) is also used for fusion of MEMS IMU and vision system that consists of a single camera and infrared LEDs that is ceiling landmarks. The fusion filter generally utilizes the position of feature points from the image as measurement. However, this method can cause position error due to the bias of MEMS IMU when the camera image is not obtained if the bias is not properly estimated through the filter. Therefore, it is proposed that the fusion method which uses the position of feature points and the velocity of the camera determined from optical flow of feature points. It is verified by experiments that the performance of the proposed method is robust to the bias of IMU compared to the method that uses only the position of feature points.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.435-442
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• 2018

This study implemented an FPGA-based system to extract PCB defect patterns. The FPGA-based system can perform pattern matching at high speed for vision automation. An image processing library that is used to extract defect patterns was also implemented in IPs to optimize the system. The IPs implemented are Camera Link IP, Histogram IP, VGA IP, Horizontal Projection IP and Vertical Projection IP. In terms of hardware, the FPGA chip from the Vertex-5 of Xilinx was used to receive and handle images that are sent from a digital camera. This system uses MicroBlaze CPU. The image results are sent to PC and displayed on a 7inch TFT-LCD and monitor.

• Korean Journal of Computational Design and Engineering
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• v.20 no.4
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• pp.375-384
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• 2015

Recently, there has been a gradual increase in the number of people who are interested in cycling, leading to an increasing number of cycling equipment consumers. However, many bicyclists get hurt because of their lack of knowledge about the right size of bicycle for their body. Although it is necessary for a rider to fit their bicycle to prevent injury, they reject a fitting service because of the long hours and high cost. In this study, we propose a bicycle fitting system that uses a depth camera to improve the limitations of existing manual fitting systems. With the defined formula, the system calculates the size of the bicycle using body image information extracted by a depth camera and visualizes a customized bicycle for a specific consumer. This system will not only save the customer time and money, but will prevent injury from the use of a bicycle that does not fit.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.742-745
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• 2009

This paper proposes a wireless LAN antenna system that tracks an object automatically by using image-based tracking. The proposed system consists of a camera and a pan-tilt unit in addition to a directional wireless LAN antenna. The camera and the directional antenna are set in same direction and they are set on the pan-tilt unit. A target object which has a wireless LAN receiver is tracked by using images captured by the camera. And the directional antenna faces in same direction as the camera by the pan-tilt unit. Therefore, the directional antenna keeps pointing the receiver, and a transmitting efficiency is improved. A result of a fundamental experiment shows that a receiver attached to a flying airship was tracked by a prototype of the proposed antenna system. The airship flied about, and the proposed antenna system was set on a roof of a building. The experimental result indicates an effectiveness of the proposed system compared to the conventional directional LAN antenna.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.31-37
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• 2018

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.723-743
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• 2016

Indoor positioning is considered an enabler for a variety of applications, the demand for an indoor positioning service has also been accelerated. That is because that people spend most of their time indoor environment. Meanwhile, the smartphone integrated powerful camera is an efficient platform for navigation and positioning. However, for high accuracy indoor positioning by using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) users' moving in large buildings. To address those issues, this paper uses the TC-OFDM for calculating the coarse positioning information includes horizontal and altitude information for assisting smartphone camera-based positioning. Moreover, a unified representation model of image features under variety of scenarios whose name is FAST-SURF is established for computing the fine location. Finally, an optimization marginalized particle filter is proposed for fusing the positioning information from TC-OFDM and images. The experimental result shows that the wide location detection accuracy is 0.823 m (1σ) at horizontal and 0.5 m at vertical. Comparing to the WiFi-based and ibeacon-based positioning methods, our method is powerful while being easy to be deployed and optimized.

• Journal of the Korean Graphic Arts Communication Society
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• v.28 no.2
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• pp.117-128
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• 2010

Advancements in digital image have put high quality digital camera into the hands of many image professionals and consumers alike. High quality digital camera images consist originally of raw which have a set of color rendering operation applied to them to produce good images. With color rendering, the raw file was converted to Adobe RGB and sRGB color space. Also color rendering can incorporate factor such as white balance, contrast, saturation. Therefore, in this paper we conduct a study on production of optimum profile considered color rendering in digital camera. To do the experiment, the images were Digital ColorChecker SG target and ColorChecker DC target. A profiling tool was ProfileMaker 5.03. The results were analyzed by comparing in color gamut of $CIEL^*a^*b^*$ color space and calculating ${\Delta}E^*_{ab}$. Also results were analyzed in terms of different $CIEL^*a^*b^*$ color space quadrants based on lightness, chroma.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.229-235
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• 2011

To make a robust object tracking and identifying system for an intelligent robot and/or home system, heterogeneous sensor fusion between visible ray system and infrared ray system is proposed. The proposed system separates the object by combining the ROI (Region of Interest) estimated from two different images based on a heterogeneous sensor that consolidates the ordinary CCD camera and the IR (Infrared) camera. Human's body and face are detected in both images by using different algorithms, such as histogram, optical-flow, skin-color model and Haar model. Also the pose of human body is estimated from the result of body detection in IR image by using PCA algorithm along with AdaBoost algorithm. Then, the results from each detection algorithm are fused to extract the best detection result. To verify the heterogeneous sensor fusion system, few experiments were done in various environments. From the experimental results, the system seems to have good tracking and identification performance regardless of the environmental changes. The application area of the proposed system is not limited to robot or home system but the surveillance system and military system.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.206-210
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• 2011

Vision-based robot localization is challenging due to the vast amount of visual information available, requiring extensive storage and processing time. To deal with these challenges, we propose the use of features extracted from omni-directional panoramic images and present a method for localization of a mobile robot equipped with an omni-directional camera. The core of the proposed scheme may be summarized as follows : First, we utilize an omni-directional camera which can capture instantaneous $360^{\circ}$ panoramic images around a robot. Second, Nodes around the robot are extracted by the correlation coefficients of Circular Horizontal Line between the landmark and the current captured image. Third, the robot position is determined from the locations by the proposed correlation-based landmark image matching. To accelerate computations, we have assigned the node candidates using color information and the correlation values are calculated based on Fast Fourier Transforms. Experiments show that the proposed method is effective in global localization of mobile robots and robust to lighting variations.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.25-32
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• 2010

The paper proposes a hierarchical fault detection method for the high voltage equipment using a microphone array which detects the location of fault and the thermal imaging and CCD cameras which verifies the fault and stores the image, respectively. There are partial arc discharges on the faulty insulators, which generates a specific pattern of sound. Detecting the signal using the microphone array, the location of the faulty insulator can be estimated. The 6th band-pass filter was applied to remove noise signal from wind or external influence. When the mobile robot carries the thermal and CCD cameras to the possible place of the fault insulator, the fault insulators or power transmission wires can be detected by the thermal images, which are caused by the aging or natural erosion. Finally, the CCD camera captures the image of the fault insulator for the record. The detection scheme of fault location using the microphone array and the thermal images have been proved to be effective through the real experiments. As a result of this research, it becomes possible to use a mobile robot with the integrated sensors to detect the fault insulators instead of a human being.