• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1909-1918
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• 2016

This paper presents a unified framework for joint Convolutional Neural Network (CNN) based vehicle detection by leveraging multi-spectral image pairs. With the observation that under challenging environments such as night vision and limited light source, vehicle detection in a single color image can be more tractable by using additional far-infrared (FIR) image, we design joint CNN architecture for both RGB and FIR image pairs. We assume that a score map from joint CNN applied to overall image can be considered as confidence of vehicle existence. To deal with various scale ratios of vehicle candidates, multi-scale images are first generated scaling an image according to possible scale ratio of vehicles. The vehicle candidates are then detected on local maximal on each score maps. The generation of overlapped candidates is prevented with non-maximal suppression on multi-scale score maps. The experimental results show that our framework have superior performance than conventional methods with a joint framework of multi-spectral image pairs reducing false positive generated by conventional vehicle detection framework using only single color image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.437-438
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• 2011

Spectral segmentation is a major trend in image segmentation. Specially, constrained spectral segmentation, inspired by the user-given inputs, remains its challenging task. Since it makes use of the spectrum of the affinity matrix of a given image, its overall quality depends mainly on how to design the graphical model. In this work, we propose a sparse, multi-layer graphical model, where the pixels and the over-segmented regions are the graph nodes. Here, the graph affinities are computed by using the must-link and cannot-link constraints as well as the likelihoods that each node has a specific label. They are then used to simultaneously cluster all pixels and regions into visually coherent groups across all layers in a single multi-layer framework of Normalized Cuts. Although we incorporate only the adjacent connections in the multi-layer graph, the foreground object can be efficiently extracted in the spectral framework. The experimental results demonstrate the relevance of our algorithm as compared to existing popular algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1188-1202
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• 2012

In this paper, we propose a new multi-scale connected coherence tree algorithm (MCCTA) by improving the connected coherence tree algorithm (CCTA). In contrast to many multi-scale image processing algorithms, MCCTA works on multiple scales space of an image and can adaptively change the parameters to capture the coarse and fine level details. Furthermore, we design a Multi-scale Connected Coherence Tree algorithm plus Spectral graph partitioning (MCCTSGP) by combining MCCTA and Spectral graph partitioning in to a new framework. Specifically, the graph nodes are the regions produced by CCTA and the image pixels, and the weights are the affinities between nodes. Then we run a spectral graph partitioning algorithm to partition on the graph which can consider the information both from pixels and regions to improve the quality of segments for providing image segmentation. The experimental results on Berkeley image database demonstrate the accuracy of our algorithm as compared to existing popular methods.

• Steel and Composite Structures
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• v.19 no.3
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• pp.697-711
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• 2015

It is well known the importance of considering hysteretic energy demands for the seismic assessment and design of structures. In such a way that it is necessary to establish new parameters of the earthquake ground motion potential able to predict energy demands in structures. In this paper, several alternative vector-valued ground motion intensity measures (IMs) are used to estimate hysteretic energy demands in steel framed buildings under long duration narrow-band ground motions. The vectors are based on the spectral acceleration at first mode of the structure Sa($T_1$) as first component. As the second component, IMs related to peak, integral and spectral shape parameters are selected. The aim of the study is to provide new parameters or vector-valued ground motion intensities with the capacity of predicting energy demands in structures. It is concluded that spectral-shape-based vector-valued IMs have the best relation with hysteretic energy demands in steel frames subjected to narrow-band earthquake ground motions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.322-340
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• 2012

Orthogonal Frequency Division Multiplexing (OFDM) is usually regarded as a spectral efficient multicarrier modulation technique, yet it suffers from a high peak-to-average power ratio (PAPR) problem. Among all the existing PAPR reduction techniques in OFDM systems, side information based PAPR reduction techniques such as partial transmit sequence (PTS) and selective mapping (SLM) schemes, have attracted the most attention. However, the transmission of side information results in somewhat spectral loss and this does not significantly improve the bit error rate (BER) performance. Parallel combinatory (PC) OFDM yields higher spectral efficiency (SE) and better BER performance on Gaussian channels,while is a little but not obvious PAPR improvement over the ordinary OFDM system. This investigation aimed to design a 'perfect' OFDM system. We introduce the side information to rotate the subcarrier phases of our novel PC-OFDM system structure, and call this new system the SIPC(Side information based Parallel Combinatory)-OFDM system. The proposed system achieves better PAPR and SE performance. In addition, considering the tradeoff of system parameters, the proposed system also has the properties of a higher BER.

• Electronics and Telecommunications Trends
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• v.8 no.2
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• pp.69-91
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• 1993

In the conventional speech processing, the technique of FFT(Fast Fourier Transform) is usually applied to the finite number of samples within the window of specified length using the fixed sampling rate. In this case, the temporal resolution is dependent upon the length of window while the spectral resolution is dependent upon the number of samples within the window. Thus, once the temporal resolution is determined the spectral resolution is also determined or vice versa. To resolve this type of dilemma, a new type of bank-filter similar to the characteristics of cochlear model needs to be considered. Furthermore, wide dynamic range of cochlea certainly helps the stable extraction of speech features. In the paper, the human auditory system will be briefly introduced and previous works on auditory preprocessors based on cochlear model will be reviewed. As a conclusion, the design considerations of auditory preprocessors based on cochlear model will be addressed.

• 한국정보통신설비학회:학술대회논문집
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• 2002.08a
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• pp.21-23
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• 2002

In millimeter wave applications, it is often necessary to use transitions between waveguide and planar circuits. Finline structures can be used effectively to this purpose. In multilayered case, it is necessary to analyze the structure with numerical method such as spectral domain immittance method. The design procedure uses tile cutoff frequency for each taper width. The dispersion data in a single layer are compared with those in literature. The performance of the designed finline taper is verified with the FEM simulation using HFSS.

• Journal of the Optical Society of Korea
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• v.4 no.2
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• pp.79-85
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• 2000

The main purpose of this paper is to present the potential of photovoltaic systems using holographic solar concentrators. A hologram used here focuses light, spectrally splits it and diverts unwanted infrared heat away from the solar cell. The output of the hologram appears as a perpendicular thin spectral line and is displaced to solar cells on both sides. To obtain optimum design conditions we used the coupled wave theory and the vector ray tracing method. The measured data showed that the diffraction efficiency was 75 ％ and the spectral bandwidth was 350 nm.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.58-66
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• 2001

GPC has been reported as a useful self-tuning control algorithm for systems with unknown time-delay and parameters. GPC is easy to understand and implement, and thus has won popularity among many practicing engineers. Despite its success, GPC does not guarantee is nominal stability. So, in this paper, GPC is rederived in frequency domain instead of in the time domain to guarantee its nominal stability. Derivation of GPC in frequency domain involves spectral factorization and Diophantine equation. Frequency domain GPC control law is stable because the zeros of characteristic polynomial are strictly Schur. Recursive least square algorithm is used to identify unknown parameters. To see the effectiveness of the proposed controller, the controller is simulated for a numerical problem that changes in dead-time, in order and in parameters.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.154.1-154.1
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• 2011

IGRINS (Immersion Grating Infrared Spectrometer) is a cross-dispersed high resolution near-infrared spectrograph whose primary disperser is a silicon immersion grating (SIG) and cross-dispersers are two volume phase holographic gratings (VPHG). IGRINS covers the full ranges of H and K astronomical wavelength bands at a single exposure with the spectral resolution of 40,000. The overall layout of the IGRINS Cryostat is a $960{\times}600{\times}380$ cubic millimeter rectangular box and the whole optical train is sitting on an $880{\times}520{\times}50\;mm^3$ rectangular Optical Bench. The total volume of the instrument has been revolutionarily reduced and remained compact for the spectral coverage and sensitivity of a high resolution spectrograph in infrared. We, in this presentation, introduce the design models, the structural and thermal analysis results of the mechanics and cryogenics of IGRINS.