• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.246-253
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• 2016

Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.12-16
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• 2002

The clear sky radiative forcings of aerosols were evaluated over East Asia. We first investigated optical characteristics of aerosol using sky radiation measurements. An algorithm of Nakajima et al. (1996) is used for retrieving aerosol parameters such as optical thickness, ${\AA}$ngstr$\"{O}$m exponent, single scattering albedo, and size distribution from sky-radiation measurements, which then can be used for examining spatial and temporal variations of aerosol. Obtaining aerosol radiative forcing at TOA and surface, a radiative transfer model is used with inputs of obtained aerosol parameters and GMS-5 satellite-based cloud optical properties. Results show that there is a good agreement of simulated downwelling radiative flux at the surface with observation within 10 W m$^{-2}$ rms errors under the clear sky condition. However, a relatively large difference up to 40 W m$^{-2}$ rms error is found under the cloudy sky condition. The computed aerosol radiative forcing at the surface shows downward flux changes ranging from -100 to -170 W m$^{-2}$ per unit aerosol optical thickness at 0.7 $\mu$m. The different values of aerosol radiative forcing among the stations is mainly due to the differences in single scattering albedo ($\omega$$_{0.7}$) and asymmetric parameter (g$_1$) related to the geographical and seasonal variations.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.107-116
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• 2004

A GIS-based paddy inundation simulation system which is capable of simulating temporal and spatial inundation processes was established and applied in this paper. The system is composed of HEC-GeoHMS, and HEC-GeoRAS modules which interface the GIS and flood runoff models, and HEC-HMS, and HEC-RAS models which estimate the flood runoff. It was used to simulate storm runoff and inundation for a small rural watershed, the Baran HP#7, which is 10.69 $km^2$ in size. The simulated peak runoff, time to peak, and total direct runoff for eight storms were compared with the observed data. The results showed that the coefficient of determination ($R^2$) for the observed peak runoff was 0.99 and an error, RMSE, 11.862 $m^3$/s for calibration stages. In the model verification, $R^2$ was 0.99 and RMSE 1.296 $m^3$/s. Paddy inundation for each paddy growing stages in study watershed were estimated using verified inundation simulation system when probability rainfall was applied.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.9
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• pp.1172-1177
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• 1999

Comparisons of measured turbulence properties in the unburned gas region of turbulent premixed flame stabilized by pilot flame, in cases of combusting and non-combusting flow conditions, are presented. Methane-air premixed jet at fuel equivalence ratio of 0.6 and 1.0 and Reynolds number of 7,000 was diagnosed using two-color laser velocimeter to obtain turbulence statistics. Same set of measurements was repeated at 21 locations within the unburned gas region of both combusting and non-combusting conditions. Velocity data were analyzed to evaluate the spatial distribution of turbulence properties including Reynolds stress, probability densities, joint probability densities and auto correlations. Contrary to assumptions of current theoretical models, significant influence of flame was observed in every property that was studied in the present investigation. The effective viscosity increased ten-fold when flame was on from cold flow values. The effect of mixing on joint probability as well as in turbulence intensity was suppressed by the flame. The measurements suggest that common assumptions of premixed flame model may result in sizable error in prediction of flame length and temperature distribution in near-field.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.211-220
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• 2015

Recently, model-based iterative reconstruction (MBIR) has played an important role in transmission tomography by significantly improving the quality of reconstructed images for low-dose scans. MBIR is based on the penalized-likelihood (PL) approach, where the penalty term (also known as the regularizer) stabilizes the unstable likelihood term, thereby suppressing the noise. In this work we further improve MBIR by using a more expressive regularizer which can restore the underlying image more accurately. Here we used a spline regularizer derived from a linear combination of the two-dimensional splines with first- and second-order spatial derivatives and applied it to a non-quadratic convex penalty function. To derive a PL algorithm with the spline regularizer, we used a separable paraboloidal surrogates algorithm for convex optimization. The experimental results demonstrate that our regularization method improves reconstruction accuracy in terms of both regional percentage error and contrast recovery coefficient by restoring smooth edges as well as sharp edges more accurately.

• Proceedings of the KSRS Conference
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• v.2
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• pp.684-687
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• 2006

Airborne imagery must be precisely orthorectified to be used as geographical information data. GPS/INS (Global Positioning System/Inertial Navigation System) and LIDAR (LIght Detection And Ranging) data were employed to automatically orthorectify airborne images. In this study, 154 frame airborne images and LIDAR vector data were acquired. LIDAR vector data were converted to raster image for employing as reference data. To derive images with constant brightness, flat field correction was applied to the whole images. The airborne images were geometrically corrected by calculating internal orientation and external orientation using GPS/INS data and then orthorectified using LIDAR digital elevation model image. The precision of orthorectified images was validated using 50 ground control points collected in arbitrary selected five images and LIDAR intensity image. In validation results, RMSE (Root Mean Square Error) was 0.365 smaller then two times of pixel spatial resolution at the surface. It is possible that the derived mosaicked airborne image by this automatic orthorectification method is employed as geographical information data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.3
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• pp.85-90
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• 1988

A probabilistic model for the failure in a homogeneous soil slope is presented. The Safety of the slope is measured through its probability of failure rather than the customary factor of safety. The safety margin of slope failure is assumed to follow a normal distribution. Sources of uncertainties affecting characterization of soil property in a homogeneous soil layer include inherent spatial variability., estimation error from insufficient samples, and measurement errors. Uncertainties of the shear strength-along potential failure surface are expressed by one-dimensional random field models. The rupture surface, created at toe of a soil slope, has been considered to propagate towards the boundary along a path following an exponential (log-spiral) law. Having derived the statistical characteristics of the rupture surface and of the forces which act along it, the probability of failure of the slope was found. Finally the developed procedure has been applied in a case study to yield the reliability of a soil slope.

• Economic and Environmental Geology
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• v.25 no.1
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• pp.73-77
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• 1992

This paper compares numerical quadrature techniques for computing an inverse Fourier transform integral in two-dimensional resistivity modeling. The quadrature techniques using exponential and cubic spline interpolations are examined for the case of a homogeneous earth model. In both methods the integral over the interval from 0 to ${\lambda}_{min}$, where ${\lambda}_{min}$, is the minimum sampling spatial wavenumber, is calculated by approximating Fourier transformed potentials to a logarithmic function. This scheme greatly reduces the inverse Fourier transform error associated with the logarithmic discontinuity at ${\lambda}=0$. Numrical results show that, if the sampling intervals are adequate, the cubic spline interpolation method is more accurate than the exponential interpolation method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4170-4188
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• 2014

In this study, we present a denoising algorithm for high-frame-rate videos in an ultra-low illumination environment on the basis of Kalman filtering model and a new motion segmentation scheme. The Kalman filter removes temporal noise from signals by propagating error covariance statistics. Regarded as the process noise for imaging, motion is important in Kalman filtering. We propose a new motion estimation scheme that is suitable for serious noise. This scheme employs the small motion vector characteristic of high-frame-rate videos. Small changing patches are intentionally neglected because distinguishing details from large-scale noise is difficult and unimportant. Finally, a spatial bilateral filter is used to improve denoising capability in the motion area. Experiments are performed on videos with both synthetic and real noises. Results show that the proposed algorithm outperforms other state-of-the-art methods in both peak signal-to-noise ratio objective evaluation and visual quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.6
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• pp.545-555
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• 1991

In this paper, We discuss optical implementation of new optical adaptive patern recognition system based on single layer perception with learning capability and associative memory model having error corrective capability. The single layer perceptron is optically implemented by using 2 D LCTV spatial light modulators through the nonlinear quantization and polarization encoding methods, and 2 D hopfield associative memory is also implemented by using multifocus holographic lens. From some experimental results on classfication of Arabic numbers into even & edd numbers, it is shown that the proposed system can classify the patterns to the right classes correctly even for the partial and erronenous input patterns. Accordingly, the proposed optical adaptive pattern recognition system can be suggested for practical application in the fields of image processing and pattern recognition.