• Journal of the Korean Society of Visualization
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• v.21 no.3
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• pp.85-92
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• 2023

In this study, we present experimental results of cavitating flow around a vortex generator which is used to improve the flow in the wake of ships and enhance propulsion efficiency. We conducted experiments at the CNU cavitation tunnel on a total of six vortex generators, two different aspect ratios and three taper ratios. We recorded cavity patterns using a high-speed camera and quantitatively evaluated cavity fraction using OpenCV. The most important finding of this study is that the vortex cavity generated at a root leading edge of the vortex generator develops at a specific angle.

• Journal of Information Processing Systems
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• v.20 no.1
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• pp.24-37
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• 2024

To address the requirement for high-speed encryption of large amounts of data, this study improves the widely adopted cipher block chaining (CBC) mode and proposes a controllable parallel cipher block chaining (CPCBC) block cipher mode of operation. The mode consists of two phases: extension and parallel encryption. In the extension phase, the degree of parallelism n is determined as needed. In the parallel encryption phase, n cipher blocks generated in the expansion phase are used as the initialization vectors to open n parallel encryption chains for parallel encryption. The security analysis demonstrates that CPCBC mode can enhance the resistance to byte-flipping attacks and padding oracle attacks if parallelism n is kept secret. Security has been improved when compared to the traditional CBC mode. Performance analysis reveals that this scheme has an almost linear acceleration ratio in the case of encrypting a large amount of data. Compared with the conventional CBC mode, the encryption speed is significantly faster.

• Progress in Medical Physics
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• v.24 no.2
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• pp.85-91
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• 2013

At present, megavoltage computed tomography (MVCT) is the only method used to correct the position of tomotherapy patients. MVCT produces extra radiation, in addition to the radiation used for treatment, and repositioning also takes up much of the total treatment time. To address these issues, we suggest the use of a video image-guided setup (VIGS) system for correcting the position of tomotherapy patients. We developed an in-house program to correct the exact position of patients using two orthogonal images obtained from two video cameras installed at $90^{\circ}$ and fastened inside the tomotherapy gantry. The system is programmed to make automatic registration possible with the use of edge detection of the user-defined region of interest (ROI). A head-and-neck patient is then simulated using a humanoid phantom. After taking the computed tomography (CT) image, tomotherapy planning is performed. To mimic a clinical treatment course, we used an immobilization device to position the phantom on the tomotherapy couch and, using MVCT, corrected its position to match the one captured when the treatment was planned. Video images of the corrected position were used as reference images for the VIGS system. First, the position was repeatedly corrected 10 times using MVCT, and based on the saved reference video image, the patient position was then corrected 10 times using the VIGS method. Thereafter, the results of the two correction methods were compared. The results demonstrated that patient positioning using a video-imaging method ($41.7{\pm}11.2$ seconds) significantly reduces the overall time of the MVCT method ($420{\pm}6$ seconds) (p<0.05). However, there was no meaningful difference in accuracy between the two methods (x=0.11 mm, y=0.27 mm, z=0.58 mm, p>0.05). Because VIGS provides a more accurate result and reduces the required time, compared with the MVCT method, it is expected to manage the overall tomotherapy treatment process more efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2251-2259
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• 2009

We propose an algorithm and system which generates 3D stereo image by composition of 2D image from 4 multiple clusters which 1 cluster was composed of 4 multiple cameras based on network. Proposed Schemes have a network-based client-server architecture for load balancing of system caused to process a large amounts of data with real-time as well as multiple cluster environments. In addition, we make use of JPEG compression and RAM disk method for better performance. Our scheme first converts input images from 4 channel, 16 cameras to binary image. And then we generate 3D stereo images after applying edge detection algorithm such as Sobel algorithm and Prewiit algorithm used to get disparities from images of 16 multiple cameras. With respect of performance results, the proposed scheme takes about 0.05 sec. to transfer image from client to server as well as 0.84 to generate 3D stereo images after composing 2D images from 16 multiple cameras. We finally confirm that our scheme is efficient to generate 3D stereo images in multiple view and multiple clusters environments with real-time.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.57-65
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• 2009

This paper presents the image contrast enhancement technique suitable for local dimming backlight of small-sized mobile display while achieving the reduction of the power consumption. In addition to the large-sized TFT-LCD, small-sized one has adopted LED for backlight. Since, conventionally, LED was mounted on the side edge of a display panel, global dimming method has been widely used. However, recently, new advanced method of local dimming by placing the LED to the backside of the display panel and it raised the necessity of sub-blocked processing after partitioning the target image. When the sub-blocked image has low brightness, the supply current of a backlight LED is reduced, which gives both enhancement of contrast ratio and power consumption reduction. In this paper, we propose simple and improved image enhancement algorithm suitable for the small-sized mobile display. After partitioning the input image by equal sized blocks and analyzing the pixel information in each block, we realize the primary contrast enhancement by independently processing the sub-blocks using the information such as histogram, mean, and standard deviation values of luminance(Y) component. And then resulting information is transferred to each backlight control unit for local dimming to realize the secondary contrast enhancement as well as reduction of power consumption.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.4
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• pp.55-62
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• 2007

This paper proposes a defective pixel detection algorithm and its hardware structure for CCD/CMOS image sensor. In previous algorithms, the characteristics of image have not been considered. Also, some algorithms need quite a time to detect defective pixels. In order to make up for those disadvantages, the proposed defective pixel detection method detects defective pixels efficiently by considering the edges in the image and verifies them using several frames while checking scene-changes. Whenever scene-change is occurred, potentially defective pixels are checked and confirmed whether it is defective or not. Test results showed that the correct detection rate in a frame was increased 6% and the defective pixel verification time was decreased 60%. The proposed algorithm was implemented with verilog HDL. The edge indicator in color interpolation block was reused. Total logic gate count was 5.4k using 0.25um CMOS standard cell library.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2615-2628
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• 1997

In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.

• Tunnel and Underground Space
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• v.29 no.3
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• pp.184-196
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• 2019

This study aims to extract a 3D image of micro-cracks generated by hydraulic fracturing tests, using the deep learning method and X-ray computed tomography images. The pixel-level cracks are difficult to be detected via conventional image processing methods, such as global thresholding, canny edge detection, and the region growing method. Thus, the convolutional neural network-based encoder-decoder network is adapted to extract and analyze the micro-crack quantitatively. The number of training data can be acquired by dividing, rotating, and flipping images and the optimum combination for the image augmentation method is verified. Application of the optimal image augmentation method shows enhanced performance for not only the validation dataset but also the test dataset. In addition, the influence of the original number of training data to the performance of the deep learning-based neural network is confirmed, and it leads to succeed the pixel-level crack detection.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.139-146
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• 2016

Recently, popularity of 3D technology has been growing significantly and it has many application parts in the various fields of industry. In order to overcome the limitations of 2D machine vision technologies based on 2D image, we need the 3D measurement technologies. There are many 3D measurement methods as such scanning probe microscope, phase shifting interferometry, confocal scanning microscope, white-light scanning interferometry, and so on. In this paper, we have used the extended depth of focus (EDF) algorithm among 3D measurement methods. The EDF algorithm is the method which extracts the 3D information from 2D images acquired by short range depth camera. In this paper, we propose the EDF algorithm using the edge informations of images and the average values of all pixel on z-axis to improve the performance of conventional method. To verify the performance of the proposed method, we use the various synthetic images made by point spread function(PSF) algorithm. We can correctly make a comparison between the performance of proposed method and conventional one because the depth information of these synthetic images was known. Through the experimental results, the PSNR of the proposed algorithm was improved about 1 ~ 30 dB than conventional method.