• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.4
• /
• pp.586-591
• /
• 2010

In this paper, we propose the localization method of mobile robot using SURF(Speeded-Up Robust Features) and Particle filter. The proposed method is as follows: First, we seek the Landmark from the obtained image using SURF in order to find the first rigorous position of mobile robot. Second, we obtain the distance from obstacles using ultrasonic sensors in order to create the relative position of mobile robot. And then, we estimate the localization of mobile robot using Particle filter about movement of mobile robot. Finally, we show the feasibility of the proposed method through some experiments.

• Journal of the Institute of Convergence Signal Processing
• /
• v.5 no.3
• /
• pp.181-189
• /
• 2004

This paper describes the method for detecting vehicles in the rear and rear-side at night by using headlight features. A headlight is the outstanding feature that can be used to discriminate a vehicle from a dark background. In the segmentation process, a night image is transformed to a binary image that consists of black background and white regions by gray-level thresholding, and noise in the binary image is eliminated by a morphological operation. In the feature extraction process, the geometric features and moment invariant features of a headlight are defined, and they are measured in each segmented region. Regions that are not appropriate to a headlight are filtered by using geometric feature measurement. In region classification, a pair of headlights is detected by using relational features based on the symmetry of a pair of headlights. Experimental results show that this method is very applicable to an approaching vehicle detection system at nighttime.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.705-707
• /
• 2017

Stereo-based spatial radiation detection devices can obtain not only spatial distribution information about the radiation source but also distance information from the detection device to the source. And it provides more efficient information on the source than the existing radiation imaging device. In order to provide high-speed information on the spectrum and type of gamma-ray source, a high-sensitivity detection sensor with high sensitivity is required, and a technique capable of solving the saturation phenomenon at a high dose is needed. In this paper, we constructed a high sensitivity sensor for the measurement of multiple gamma - ray spatial distributions using improved function of detection module to solve saturation to high dose and conducted research to increase the scope of a single detector. The result of this paper improves the performance of gamma ray.

• Journal of IKEEE
• /
• v.25 no.4
• /
• pp.634-643
• /
• 2021

In this paper, an FPGA-based acceleration scheme of range Doppler algorithm (RDA) is proposed for the real time synthetic aperture radar (SAR) imaging. Hardware architectures of matched filter based on systolic array architecture and a high speed sinc interpolator to compensate range cell migration (RCM) are presented. In addition, the proposed hardware was implemented and accelerated on Xilinx Alveo FPGA. Experimental results for 4096×4096-size SAR imaging showed that FPGA-based implementation achieves 2 times acceleration compared to GPU-based design. It was also confirmed the proposed design can be implemented with 60,247 CLB LUTs, 103,728 CLB registers, 20 block RAM tiles and 592 DPSs at the operating frequency of 312 MHz.

• Journal of the Korean Society of Radiology
• /
• v.15 no.7
• /
• pp.935-942
• /
• 2021

Involuntary movement of internal organs by respiration is a factor that greatly affects the results of radiotherapy and diagnosis. In this study, a moving phantom was fabricated to simulate the movement of an organ or a tumor according to respiration, and ¹⁸F-FDG PET/CT scan images were acquired under various respiratory simulating conditions to analyze the movement range of the tumor movement by respiration, the level of artifacts according to the size of the tumor and the maximum standardized uptake value (SUVmax). Based on Windows CE 6.0 as the operating system, using electric actuator, electric actuator positioning driver, and programmable logic controller (PLC), the position and speed control module was operated normally at a moving distance of 0-5 cm and 10, 15, and 20 reciprocations. For sphere diameters of 10, 13, 17, 22, 28, and 37 mm at a delay time of 100 minutes, 80.4%, 99.5%, 107.9%, 113.1%, 128.0%, and 124.8%, respectively were measured. When the moving distance was the same, the difference according to the respiratory rate was insignificant. When the number of breaths is 20 and the moving distance is 1 cm, 2 cm, 3 cm, and 5 cm, as the moving distance increased at the sphere diameters of 10, 13, 17, 22, 28, and 37 mm, the ability to distinguish images from smaller spheres deteriorated. When the moving distance is 5 cm compared to the still image, the maximum values of the standard intake coefficient were 18.0%, 23.7%, 29.3%, 38.4%, 49.0%, and 67.4% for sphere diameters of 10, 13, 17, 22, 28, and 37 mm, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.6
• /
• pp.110-123
• /
• 2019

Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.

• Smart Media Journal
• /
• v.2 no.4
• /
• pp.60-65
• /
• 2013

In this paper, we propose a high-resolution disparity map generation method using a low-resolution time-of-flight (TOF) depth camera and color camera. The TOF depth camera is efficient since it measures the range information of objects using the infra-red (IR) signal in real-time. It also quantizes the range information and provides the depth image. However, there are some problems of the TOF depth camera, such as noise and lens distortion. Moreover, the output resolution of the TOF depth camera is too small for 3D applications. Therefore, it is essential to not only reduce the noise and distortion but also enlarge the output resolution of the TOF depth image. Our proposed method generates a depth map for a color image using the TOF camera and the color camera simultaneously. We warp the depth value at each pixel to the color image position. The color image is segmented using the mean-shift segmentation method. We define a cost function that consists of color values and segmented color values. We apply a weighted average filter whose weighting factor is defined by the random walk probability using the defined cost function of the block. Experimental results show that the proposed method generates the depth map efficiently and we can reconstruct good virtual view images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.780-781
• /
• 2016

The stereo radiation detection system detects gamma ray source and measures the two dimensional distribution image based on the detection result. Then the system is implemented to measure the distance to the radiation source from the system in 3D space using stereo vision algorithm. In this paper, we reduced the time for a gamma-ray scan space detection through image processing algorithms. In addition, it combines radiation and visible light images. Then we conducted a study for improving the distribution of gamma-ray detection efficiency through the stereo calibration using a 3D visualization. As a result, we obtain an improved detection time by more than 30% and have acquired a visible image with a 3D monitor.

• Journal of KIISE:Software and Applications
• /
• v.37 no.2
• /
• pp.110-119
• /
• 2010

In this paper, we propose an automatic segmentation of the prostate using intensity distribution and gradient information in MR images. First, active shape model using adaptive intensity profile and multi-resolution technique is used to extract the prostate surface. Second, hole elimination using geometric information is performed to prevent the hole from occurring by converging the surface shape to the local optima. Third, the surface shape with large anatomical variation is corrected by using 2D gradient information. In this case, the corrected surface shape is often represented as rugged shape which is generated by the limited number of vertices. Thus, it is reconstructed by using surface modelling and smoothing. To evaluate our method, we performed the visual inspection, accuracy measures and processing time. For accuracy evaluation, the average distance difference and the overlapping volume ratio between automatic segmentation and manual segmentation by two radiologists are calculated. Experimental results show that the average distance difference was 0.3${\pm}$0.21mm and the overlapping volume ratio was 96.31${\pm}$2.71%. The total processing time of twenty patient data was 16 seconds on average.

• Journal of the Institute of Convergence Signal Processing
• /
• v.18 no.2
• /
• pp.68-75
• /
• 2017

This study deals with a color-based tracking method of a moving object effectively in case that the color of the moving object is same as or similar to that of background. The CamShift algorithm, which is the representative color-based tracking method, shows unstable tracking when the color of moving objects exists in the background. In order to overcome the drawback, this paper proposes the CamShift algorithm merged with depth information of the object. Depth information can be obtained from Kinect device which measures the distance information of all pixels in an image. Experimental result shows that the proposed tracking method, the Camshift merged with depth information of the tracking object, makes up for the unstable tracking of the existing CamShift algorithm and also shows improved tracking performance in comparison with only CamShift algorithm.