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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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IEIE Transactions on Smart Processing and Computing
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The Institute of Electronics Engineers of Korea
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Volume & Issues
Volume 4, Issue 6 - Dec 2015
Volume 4, Issue 5 - Oct 2015
Volume 4, Issue 4 - Aug 2015
Volume 4, Issue 3 - Jun 2015
Volume 4, Issue 2 - Apr 2015
Volume 4, Issue 1 - Feb 2015
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Median Filtering Detection of Digital Images Using Pixel Gradients
RHEE, Kang Hyeon ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 195~201
DOI : 10.5573/IEIESPC.2015.4.4.195
For median filtering (MF) detection in altered digital images, this paper presents a new feature vector that is formed from autoregressive (AR) coefficients via an AR model of the gradients between the neighboring row and column lines in an image. Subsequently, the defined 10-D feature vector is trained in a support vector machine (SVM) for MF detection among forged images. The MF classification is compared to the median filter residual (MFR) scheme that had the same 10-D feature vector. In the experiment, three kinds of test items are area under receiver operating characteristic (ROC) curve (AUC), classification ratio, and minimal average decision error. The performance is excellent for unaltered (ORI) or once-altered images, such as
average filtering (AVE3), QF=90 JPEG (JPG90), 90% down, and 110% up to scale (DN0.9 and Up1.1) images, versus
median filtering (MF3 and MF5, respectively) and MF3 and MF5 composite images (MF35). When the forged image was post-altered with AVE3, DN0.9, UP1.1 and JPG70 after MF3, MF5 and MF35, the performance of the proposed scheme is lower than the MFR scheme. In particular, the feature vector in this paper has a superior classification ratio compared to AVE3. However, in the measured performances with unaltered, once-altered and post-altered images versus MF3, MF5 and MF35, the resultant AUC by 'sensitivity' (TP: true positive rate) and '1-specificity' (FN: false negative rate) is achieved closer to 1. Thus, it is confirmed that the grade evaluation of the proposed scheme can be rated as 'Excellent (A)'.
New Inference for a Multiclass Gaussian Process Classification Model using a Variational Bayesian EM Algorithm and Laplace Approximation
Cho, Wanhyun ; Kim, Sangkyoon ; Park, Soonyoung ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 202~208
DOI : 10.5573/IEIESPC.2015.4.4.202
In this study, we propose a new inference algorithm for a multiclass Gaussian process classification model using a variational EM framework and the Laplace approximation (LA) technique. This is performed in two steps, called expectation and maximization. First, in the expectation step (E-step), using Bayes' theorem and the LA technique, we derive the approximate posterior distribution of the latent function, indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. In the maximization step, we compute the maximum likelihood estimators for hyper-parameters of a covariance matrix necessary to define the prior distribution of the latent function by using the posterior distribution derived in the E-step. These steps iteratively repeat until a convergence condition is satisfied. Moreover, we conducted the experiments by using synthetic data and Iris data in order to verify the performance of the proposed algorithm. Experimental results reveal that the proposed algorithm shows good performance on these datasets.
A Simulation Study on The Behavior Analysis of The Degree of Membership in Fuzzy c-means Method
Okazaki, Takeo ; Aibara, Ukyo ; Setiyani, Lina ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 209~215
DOI : 10.5573/IEIESPC.2015.4.4.209
Fuzzy c-means method is typical soft clustering, and requires a degree of membership that indicates the degree of belonging to each cluster at the time of clustering. Parameter values greater than 1 and less than 2 have been used by convention. According to the proposed data-generation scheme and the simulation results, some behaviors in the degree of "fuzziness" was derived.
Development of Visual Odometry Estimation for an Underwater Robot Navigation System
Wongsuwan, Kandith ; Sukvichai, Kanjanapan ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 216~223
DOI : 10.5573/IEIESPC.2015.4.4.216
The autonomous underwater vehicle (AUV) is being widely researched in order to achieve superior performance when working in hazardous environments. This research focuses on using image processing techniques to estimate the AUV's egomotion and the changes in orientation, based on image frames from different time frames captured from a single high-definition web camera attached to the bottom of the AUV. A visual odometry application is integrated with other sensors. An internal measurement unit (IMU) sensor is used to determine a correct set of answers corresponding to a homography motion equation. A pressure sensor is used to resolve image scale ambiguity. Uncertainty estimation is computed to correct drift that occurs in the system by using a Jacobian method, singular value decomposition, and backward and forward error propagation.
Real-time Full-view 3D Human Reconstruction using Multiple RGB-D Cameras
Yoon, Bumsik ; Choi, Kunwoo ; Ra, Moonsu ; Kim, Whoi-Yul ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 224~230
DOI : 10.5573/IEIESPC.2015.4.4.224
This manuscript presents a real-time solution for 3D human body reconstruction with multiple RGB-D cameras. The proposed system uses four consumer RGB/Depth (RGB-D) cameras, each located at approximately
from the next camera around a freely moving human body. A single mesh is constructed from the captured point clouds by iteratively removing the estimated overlapping regions from the boundary. A cell-based mesh construction algorithm is developed, recovering the 3D shape from various conditions, considering the direction of the camera and the mesh boundary. The proposed algorithm also allows problematic holes and/or occluded regions to be recovered from another view. Finally, calibrated RGB data is merged with the constructed mesh so it can be viewed from an arbitrary direction. The proposed algorithm is implemented with general-purpose computation on graphics processing unit (GPGPU) for real-time processing owing to its suitability for parallel processing.
Analysis of Screen Content Coding Based on HEVC
Ahn, Yong-Jo ; Ryu, Hochan ; Sim, Donggyu ; Kang, Jung-Won ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 231~236
DOI : 10.5573/IEIESPC.2015.4.4.231
In this paper, the technical analysis and characteristics of screen content coding (SCC) based on High efficiency video coding (HEVC) are presented. For SCC, which is increasingly used these days, HEVC SCC standardization has been proceeded. Technologies such as intra block copy (IBC), palette coding, and adaptive color transform are developed and adopted to the HEVC SCC standard. This paper examines IBC and palette coding that significantly impacts RD performance of SCC for screen content. The HEVC SCC reference model (SCM) 4.0 was used to comparatively analyze the coding performance of HEVC SCC based on the HEVC range extension (RExt) model for screen content.
Real-time Speed Limit Traffic Sign Detection System for Robust Automotive Environments
Hoang, Anh-Tuan ; Koide, Tetsushi ; Yamamoto, Masaharu ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 237~250
DOI : 10.5573/IEIESPC.2015.4.4.237
This paper describes a hardware-oriented algorithm and its conceptual implementation in a real-time speed limit traffic sign detection system on an automotive-oriented field-programmable gate array (FPGA). It solves the training and color dependence problems found in other research, which saw reduced recognition accuracy under unlearned conditions when color has changed. The algorithm is applicable to various platforms, such as color or grayscale cameras, high-resolution (4K) or low-resolution (VGA) cameras, and high-end or low-end FPGAs. It is also robust under various conditions, such as daytime, night time, and on rainy nights, and is adaptable to various countries' speed limit traffic sign systems. The speed limit traffic sign candidates on each grayscale video frame are detected through two simple computational stages using global luminosity and local pixel direction. Pipeline implementation using results-sharing on overlap, application of a RAM-based shift register, and optimization of scan window sizes results in a small but high-performance implementation. The proposed system matches the processing speed requirement for a 60 fps system. The speed limit traffic sign recognition system achieves better than 98% accuracy in detection and recognition, even under difficult conditions such as rainy nights, and is implementable on the low-end, low-cost Xilinx Zynq automotive Z7020 FPGA.
Pair-Wise Serial ROIC for Uncooled Microbolometer Array
Haider, Syed Irtaza ; Majzoub, Sohaib ; Alturaigi, Mohammed ; Abdel-Rahman, Mohamed ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 251~257
DOI : 10.5573/IEIESPC.2015.4.4.251
This work presents modelling and simulation of a readout integrated circuit (ROIC) design considering pair-wise serial configuration along with thermal modeling of an uncooled microbolometer array. A fully differential approach is used at the input stage in order to reduce fixed pattern noise due to the process variation and self-heating-related issues. Each pair of microbolometers is pulse-biased such that they both fall under the same self-heating point along the self-heating trend line. A
process variation is considered. The proposed design is simulated with a reference input image consisting of an array of
pixels. This configuration uses only one unity gain differential amplifier along with a single 14-bit analog-to-digital converter in order to minimize the dynamic range requirement of the ROIC.
Implementation of an LFM-FSK Transceiver for Automotive Radar
Yoo, HyunGi ; Park, MyoungYeol ; Kim, YoungSu ; Ahn, SangChul ; Bien, Franklin ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 258~264
DOI : 10.5573/IEIESPC.2015.4.4.258
The first 77 GHz transceiver that applies a heterodyne structure-based linear frequency modulation-frequency shift keying (LFM-FSK) front-end module (FEM) is presented. An LFM-FSK waveform generator is proposed for the transceiver design to avoid ghost target detection in a multi-target environment. This FEM consists of three parts: a frequency synthesizer, a 77 GHz up/down converter, and a baseband block. The purpose of the FEM is to make an appropriate beat frequency, which will be the key to solving problems in the digital signal processor (DSP). This paper mainly focuses on the most challenging tasks, including generating and conveying the correct transmission waveform in the 77 GHz frequency band to the DSP. A synthesizer test confirmed that the developed module for the signal generator of the LFM-FSK can produce an adequate transmission signal. Additionally, a loop back test confirmed that the output frequency of this module works well. This development will contribute to future progress in integrating a radar module for multi-target detection. By using the LFM-FSK waveform method, this radar transceiver is expected to provide multi-target detection, in contrast to the existing method.
A Novel Red Apple Detection Algorithm Based on AdaBoost Learning
Kim, Donggi ; Choi, Hongchul ; Choi, Jaehoon ; Yoo, Seong Joon ; Han, Dongil ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 265~271
DOI : 10.5573/IEIESPC.2015.4.4.265
This study proposes an algorithm for recognizing apple trees in images and detecting apples to measure the number of apples on the trees. The proposed algorithm explores whether there are apple trees or not based on the number of image block-unit edges, and then it detects apple areas. In order to extract colors appropriate for apple areas, the CIE
color space is used. In order to extract apple characteristics strong against illumination changes, modified census transform (MCT) is used. Then, using the AdaBoost learning algorithm, characteristics data on the apples are learned and generated. With the generated data, the detection of apple areas is made. The proposed algorithm has a higher detection rate than existing pixel-based image processing algorithms and minimizes false detection.
Construction of Confusion Lines for Color Vision Deficiency and Verification by Ishihara Chart
Cho, Keuyhong ; Lee, Jusun ; Song, Sanghoon ; Han, Dongil ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 272~280
DOI : 10.5573/IEIESPC.2015.4.4.272
This paper proposes color databases that can be used for various purposes for people with a color vision deficiency (CVD). The purpose of this paper is to group colors within the sRGB gamut into the CIE
color space using the Brettel algorithm to simulate the representative colors of each group into colors visible to people with a CVD, and to establish a confusion line database by comparing colors that might cause confusion for people with different types of color vision deficiency. The validity of the established confusion lines were verified by using an Ishihara chart. The different colors that confuse those with a CVD in an Ishihara chart are located in the same confusion line database for both protanopia and deutanopia. Instead of the 3D RGB color space, we have grouped confusion colors to the CIE
space coordinates in a more distinctive and intuitive manner, and can establish a database of colors that can be perceived by people with a CVD more accurately. Editor - Highlight - Do these changes reflect the intended meaning? If not, please rephrase as intended.
A Survey of Human Action Recognition Approaches that use an RGB-D Sensor
Farooq, Adnan ; Won, Chee Sun ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 281~290
DOI : 10.5573/IEIESPC.2015.4.4.281
Human action recognition from a video scene has remained a challenging problem in the area of computer vision and pattern recognition. The development of the low-cost RGB depth camera (RGB-D) allows new opportunities to solve the problem of human action recognition. In this paper, we present a comprehensive review of recent approaches to human action recognition based on depth maps, skeleton joints, and other hybrid approaches. In particular, we focus on the advantages and limitations of the existing approaches and on future directions.
Design of High-Speed Comparators for High-Speed Automatic Test Equipment
Yoon, Byunghun ; Lim, Shin-Il ;
IEIE Transactions on Smart Processing and Computing, volume 4, issue 4, 2015, Pages 291~296
DOI : 10.5573/IEIESPC.2015.4.4.291
This paper describes the design of a high-speed comparator for high-speed automatic test equipment (ATE). The normal comparator block, which compares the detected signal from the device under test (DUT) to the reference signal from an internal digital-to-analog converter (DAC), is composed of a rail-to-rail first pre-amplifier, a hysteresis amplifier, and a third pre-amplifier and latch for high-speed operation. The proposed continuous comparator handles high-frequency signals up to 800MHz and a wide range of input signals (0~5V). Also, to compare the differences of both common signals and differential signals between two DUTs, the proposed differential mode comparator exploits one differential difference amplifier (DDA) as a pre-amplifier in the comparator, while a conventional differential comparator uses three op-amps as a pre-amplifier. The chip was implemented with
Bipolar CMOS DEMOS (BCDMOS) technology, can compare signal differences of 5mV, and operates in a frequency range up to 800MHz. The chip area is