• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.85-92
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• 2009

This paper proposes a full-search block-matching motion estimation circuit with hybrid architecture combining systolic arrays and adder trees for an MPEG-4 encoder. The proposed circuit uses systolic arrays for motion estimation with a small number of clock cycles and adder trees to reduce required circuit resources. The interpolation circuit for 1/2 pixel motion estimation consists of six adders, four subtracters and ten registers. We improved the circuit performance by resource sharing and efficient scheduling techniques. We described the motion estimation circuit for integer and 1/2 pixels at RTL in Verilog HDL. The logic-level circuit synthesized by using 130nm standard cell library contains 218,257 gates and can process 94 D1($720{\times}480$) image frames per second.

• Spatial Information Research
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• v.21 no.3
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• pp.31-43
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• 2013

Although the vector map data possesses much higher values than other types of multimedia, the data copyright and the protection against illegal duplication are still far away from the attention. This paper proposes a novel watermarking technique which is both robust to diverse attacks and optimized to a vector map structure. Six approaches are proposed for the design of the watermarking algorithm: point-based approach, building a minimum perimeter triangle, watermark embedding in the length ratio, referencing to the pixel position of the watermark image, grouping, and using the one-way function. Our method preserves the characteristics of watermarking such as embedding effectiveness, fidelity, and false positive rate, while maintaining robustness to all types of attack except a noise attack. Furthermore, our method is a blind scheme in which robustness is independent of the map data. Finally, our method provides a solution to the challenging issue of degraded robustness under severe simplification attacks.

• Investigative Magnetic Resonance Imaging
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• v.21 no.4
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• pp.210-222
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• 2017

Purpose: To develop a novel combination of controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) with integrated SSFP (CAIPI-iSSFP) for accelerated SSFP imaging without banding artifacts at 3T. Materials and Methods: CAIPI-iSSFP was developed by adding a dephasing gradient to the balanced SSFP (bSSFP) pulse sequence with a gradient area that results in $2{\pi}$ dephasing across a single pixel. Extended phase graph (EPG) simulations were performed to show the signal behaviors of iSSFP, bSSFP, and RF-spoiled gradient echo (SPGR) sequences. In vivo experiments were performed for brain and abdominal imaging at 3T with simultaneous multi-slice (SMS) acceleration factors of 2, 3 and 4 with CAIPI-iSSFP and CAIPI-bSSFP. The image quality was evaluated by measuring the relative contrast-to-noise ratio (CNR) and by qualitatively assessing banding artifact removal in the brain. Results: Banding artifacts were removed using CAIPI-iSSFP compared to CAIPI-bSSFP up to an SMS factor of 4 and 3 on brain and liver imaging, respectively. The relative CNRs between gray and white matter were on average 18% lower in CAIPI-iSSFP compared to that of CAIPI-bSSFP. Conclusion: This study demonstrated that CAIPI-iSSFP provides up to a factor of four acceleration, while minimizing the banding artifacts with up to a 20% decrease in the relative CNR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3295-3311
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• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.22-29
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• 2010

A real-time detection and tracking of moving objects in video sequences is very important for smart surveillance systems. In this paper, we propose a novel algorithm for the detection of moving objects that is the entropy-based adaptive Gaussian mixture model (AGMM). First, the increment of entropy generally means the increment of complexity, and objects in unstable conditions cause higher entropy variations. Hence, if we apply these properties to the motion segmentation, pixels with large changes in entropy in moments have a higher chance in belonging to moving objects. Therefore, we apply the Clausius entropy theory to convert the pixel value in an image domain into the amount of energy change in an entropy domain. Second, we use an adaptive background subtraction method to detect moving objects. This models entropy variations from backgrounds as a mixture of Gaussians. Experiment results demonstrate that our method can detect motion object effectively and reliably.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.11-21
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• 2011

This paper introduces an SIMD(Single Instruction Multiple Data) based parallel processor that efficiently processes massive data inherent in multimedia. In addition, this paper implements MMX(MultiMedia eXtension)-type instructions on the data parallel processor and evaluates and analyzes the performance of the MMX-type instructions. The reference data parallel processor consists of 16 processors each of which has a 32-bit datapath. Experimental results for a JPEG compression application with a 1280x1024 pixel image indicate that MMX-type instructions achieves a 50% performance improvement over the baseline instructions on the same data parallel architecture. In addition, MMX-type instructions achieves 100% and 51% improvements over the baseline instructions in energy efficiency and area efficiency, respectively. These results demonstrate that multimedia specific instructions including MMX-type have potentials for widely used many-core GPU(Graphics Processing Unit) and any types of parallel processors.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.57-67
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• 2015

The concept of detection and classification of objects based on infrared camera is widely applied to military applications. While the object detection technology using infrared images has long been researched and the latest one can detect the object in sub-pixel, the object classification technology still needs more research. In this paper, we present object classification method based on measured radiant intensity of objects such as target, artillery, and missile using infrared camera. The suggested classification method was verified by radiant intensity measuring experiment using black body. Also, possible measuring errors were compensated by modelling-based correction for accurate radiant intensity measure. After measuring radiation of object, the model of radiant intensity is standardized based on theoretical background. Based on this research, the standardized model can be applied to the object classification by comparing with the actual measured radiant intensity of target, artillery, and missile.

• 전자공학회논문지 IE
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• v.45 no.3
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• pp.13-19
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• 2008

In this paper, we propose a new IPC(Interlace to Progressive Conversion) method based on ELA(EDge Line based Average) interpolation using detecting the reliable edge direction. Existing ELA algorithms execute linear interpolation using edge direction without considering noises. In noisy images, these algorithms degrade quality because if interpolation based on the wrong edge direction. Out scheme is able to solve the problem of existing ELA algorithms in noisy images. First, filter a noisy pixel and estimate sizes of the noiseless orginal pixed and the noise, repectively. Then, considering the size of the noise, calculate weights of ELA and vertical interpolation. If noises exist after IPC, these could be eliminated by post filtering. The experimental results show that our proposed algorithm has about $1{\sim}2$ dB better performance than those of existing ELA algorithms.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.488-493
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• 2011

The Korean spine geometry and property data for researchers were made by KISTI and Catholic Institute for Applied Anatomy. We took whole spine CT, X-Ray, BMD scan for making high resolution cross-sectional spine images using more 20 donated cadavers(60 - 80 years). Then we constructed 3-dimensional volume model using serial CT images by Mimics software. The major morphometric parameters of vertebrae were measured. Mechanical motion and property data were obtained by the same cadavers using the DEXA for BMD and the spine simulator. The Korean spine geometry and property data could be used for research and development of medical device.

• Journal of Korea Multimedia Society
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• v.9 no.10
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• pp.1304-1313
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• 2006

Biometric-based authentication can provide strong security guarantee about the identity of users. However, security of biometric data is particularly important as the compromise of the data will be permanent. In this paper, we propose a secure and efficient protocol to transmit fingerprint images from a fingerprint sensor to a client by exploiting characteristics of fingerprint images. Because the fingerprint sensor is computationally limited, however, such encryption algorithm may not be applied to the full fingerprint images in real-time. To reduce the computational workload on the resource-constrained sensor, we apply the encryption algorithm to a specific bitplane of each pixel of the fingerprint image. We use the LSB as specific bitplane instead of MSB used to encrypt general multimedia contents because simple attacks can reveal the fingerprint ridge information even from the MSB-based encryption. Based on the experimental results, our proposed algorithm can reduce the execution time of the full encryption by a factor of six and guarantee both the integrity and the confidentiality without any leakage of the ridge information.