• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.695-706
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• 2012

The purpose of this paper is to propose a service system for a digital hologram video, which has not been published yet. This system assumes the existing service frame for 2-dimensional or 3-dimensional image/video, which includes data acquisition, processing, transmission, reception, and reconstruction. This system also includes the function to service the digital hologram at the viewer's view point by tracking the viewer's face. For this function, the image information at the virtual view point corresponding to the viewer's view point is generated to get the corresponding hologram. Here in this paper, only a prototype that includes major functions of it is implemented, which includes camera system for data acquisition, camera calibration and image rectification, depth/intensity image enhancement, intermediate view generation, digital hologram generation, and holographic image reconstruction by both simulation and optical apparatus. The proposed prototype system was implemented and the result showed that it takes about 352ms to generate one frame of digital hologram and reconstruct the image by simulation, or 183ms to reconstruct image by optical apparatus instead of simulation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.92-100
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• 2006

In imaging devices such as digital cameras using a single image sensor, captured images are the sub-sampled images comprised of the pixels that have only one of the three primary colors per a pixel. This images should be restored to the color images through an image processing referred as color interpolation. In this paper, we derive relation between the average of the data from CFA image sensor and the average of each color channel data. By using this relation, a new efficient method for color interpolation is proposed. Also, in order to reduce the zipper effect in a restored image, missing luminance values are interpolated along any edges in the captured image. On the other hand, for the chrominance channel interpolation, we average difference between a chrominance value and a luminance value in a local area, and this average value is added to the pixel value of the interpolated location. The proposed method has been compared with several previous methods, and our experimental results show the better results than the other methods.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.10
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• pp.377-382
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• 2018

This study deals with internal state and tissue density analysis methods for red ginseng grade determination. For internal measurement of red ginseng, there have been various studies on nondestructive testing methods since the 1990s, It was difficult to grasp the most important inner hole and inside whites in the grading. So in this study, we developed a closed capturing device for infra-red illumination environment, and developed an internal measurement system that can detect the presence and diameter of inner hole and inside whites. Made devices consisted of infrared lights with a high transmission rate of red ginseng in 920 nanometer wave band, a infra-red camera and a Y axis actuator with a red ginseng automatically controlled focus on the camera. The proposed algorithm performs an auto-focus system on the Y-axis actuator to automatically adjust the sharp focus of the object according to the size and thickness. Then red ginseng is rotated $360^{\circ}$ at $1^{\circ}$ intervals and 360 total images are acquired, and reconstructed as a sinogram through Radon transform and Back-projection algorithm was performed to acquire internal images of red ginseng. As a result of the algorithm, it was possible to acquire internal cross-sectional image regardless of the thickness and shape of red ginseng. In the future, if more than 10,000 different shapes and sizes of red ginseng internal cross-sectional image are acquired and the classification criterion is applied, it can be used as a reliable automated ginseng grade automatic measurement method.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.175-182
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• 2017

Noises are usually generated by various external causes and low quality devices in image data acquisition and recording as well as by channel interference in image transmission. Since these noise signals result in the loss of information, subsequent image processing is subject to the corruption of the original image. In general, image processing is performed in the mixed noise environment where common types of noise, known to be Gaussian and impulse, are present. This study proposes an iterative weighted mean filter for reducing mixed type of noise. Impulse noise pixels are first turned off in the input image, then $3{\times}3$ sliding window regions are processed by replacing center pixel with the result of weighted mean mask operation. This filtering processes are iterated until all the impulse noise pixels are replaced. Applied to images corrupted by Gaussian noise with ${\sigma}=10$ and different levels of impulse noise, the proposed filtering method improved the PSNR by up to 12.98 dB, 1.97 dB, 1.97 dB respectively, compared to SAWF, AWMF, MMF when impulse noise desities are less than 60%.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.119-130
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• 2009

The aim of this study is to analyze the effects of DVR(Driving Video Recorder) operation on decreasing the number of traffic accidents, the cost of traffic accident claim, and the behavioral change in drivers' driving. The data for this research are obtained from taxi drivers in Busan. For this, Structural Equation Model and two-way ANOVA are employed for empirical analysis. Overall results of this study show that the number of traffic accidents of 4 taxi corporations in Busan has decreased by average 32.7 percent after using DVRs. In addition, as to the cost of taxi accident claims, it is expected that the DVR operation has a considerable effect on economic benefits of taxi corporations. Moreover, this study could make clear the difference in behaviors between DVR users and non-users, and discriminate the positive and negative impacts of the DVR operation on the drivers' driving behavior. The study quantitatively examined the indirect impact of 'attitude', 'subject norm' and 'behavioral control' factors on planned 'behavior', and the direct impact of 'behavioral control' factor on the planned 'behavior'. This study suggests that they should add the video recoding function of DVRs when operation recorder(blackbox for the car) is obligatorily set up on cars for business by traffic security law.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.29-42
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• 2016

Remote sensing allows acquisition of information across a large area without contacting objects, and has thus been rapidly developed by application to different areas. Thus, with the development of remote sensing, satellites are able to rapidly advance in terms of their image resolution. As a result, satellites that use remote sensing have been applied to conduct research across many areas of the world. However, while research on remote sensing is being implemented across various areas, research on data processing is presently insufficient; that is, as satellite resources are further developed, data processing continues to lag behind. Accordingly, this paper discusses plans to maximize the performance of satellite image processing by utilizing the CUDA(Compute Unified Device Architecture) Library of NVIDIA, a parallel processing technique. The discussion in this paper proceeds as follows. First, standard KOMPSAT(Korea Multi-Purpose Satellite) images of various sizes are subdivided into five types. NDVI(Normalized Difference Vegetation Index) is implemented to the subdivided images. Next, ArcMap and the two techniques, each based on CPU or GPU, are used to implement NDVI. The histograms of each image are then compared after each implementation to analyze the different processing speeds when using CPU and GPU. The results indicate that both the CPU version and GPU version images are equal with the ArcMap images, and after the histogram comparison, the NDVI code was correctly implemented. In terms of the processing speed, GPU showed 5 times faster results than CPU. Accordingly, this research shows that a parallel processing technique using CUDA Library can enhance the data processing speed of satellites images, and that this data processing benefits from multiple advanced remote sensing techniques as compared to a simple pixel computation like NDVI.

• Journal of the Korean Geotechnical Society
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• v.23 no.1
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• pp.51-65
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• 2007

The purpose of this study is the development and application of a high resolution ultrasonic wave imaging system to detect discontinuity plane in lab-scale rock models. This technique is based on received time series which capture the multiple reflections at interface. This study includes the fundamental aspects of ultrasonic wave propagation in rock mass, the selection of the optimal ultrasonic wave transducer, data gathering, a signal processing, imaging methods, and experiments. Experiments are carried out by the horizontal movement and rotation devices. Experimental studies show the discontinuity is well detected by the horizontal movement and rotation devices under water. Furthermore, the discontinuity and the cavity on the plaster block are identified by the rotation device. This study suggests that the new method may be an economical and effective tool for the detection of the discontinuity on rock mass.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.97-105
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• 2017

An air-burst munition is limited in space, so there is a limit on the size of the fuze and the amount of ammunition. In order to increase a firepower to a target with limited ammunition, it is necessary to concentrate the firepower on the ground instead of the omnidirectional explosion after flying to the target. This paper explores the design and verification of a ground-detection sensor that detects the direction of the ground and determines the flight-distance of an air-burst munition using a single axis geomagnetic sensor. Prior to the design of the ground detection sensor, a geomagnetic sensor model mounted on the spinning air-burst munition is analyzed and a ground-detection algorithm by simplifying this model is designed. A high speed rotating device to simulate a rotation environment is designed and a geomagnetic sensor and a remote-recording system are fabricated to obtain geomagnetic data. The ground detection algorithm is verified by post-processing the acquired geomagnetic data. Taking miniaturization and low-power into consideration, the ground detection sensor is implemented with analog devices and the processor. The output signal of the ground detection sensor rotating at an arbitrary rotation speed of 200 Hz is connected to the LED (Light Emitting Diode) in the high speed rotating device and the ground detection sensor is verified using a high-speed camera.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.152-164
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• 2015

A rapid development of semiconductors, sensors and mobile network technologies has enable that the embedded device includes high sensitivity sensors, wireless communication modules and a video processing module for vehicular environment, and many researchers have been actively studying the smart car technology combined on the high performance embedded devices. The vehicle is increased as the development of society, and the risk of accidents is increasing gradually. Thus, the advanced driver assistance system providing the vehicular status and the surrounding environment of the vehicle to the driver using various sensor data is actively studied. In this paper, we design and implement the smart vehicular camera device providing the V2X communication and gathering environment information. And we studied the method to create the metadata from a received video data and sensor data using video analysis algorithm. In addition, we invent S-ROI, D-ROI methods that set a region of interest in a video frame to improve calculation performance. We performed the performance evaluation for two ROI methods. As the result, we confirmed the video processing speed that S-ROI is 3.0 times and D-ROI is 4.8 times better than a full frame analysis.