• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.25-31
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• 2005

In this paper, we present a face detection system using the Support Vector Domain Description (SVDD) in color images. Conventional face detection algorithms require a training procedure using both face and non-face images. In SVDD however we employ only face images for training. We can detect faces in color images from the radius and center pairs of SVDD. We also use Entropic Threshold for extracting the facial feature and sliding window for improved performance while saving processing time. The experimental results indicate the effectiveness and efficiency of the proposed algorithm compared to conventional PCA (Principal Component Analysis)-based methods.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.37-39
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• 2009

In the research of speech recognition, locating the beginning and end of a speech utterance in a background of noise is of great importance. Since the background noise presenting to record will introduce disturbance while we just want to get the stationary parameters to represent the corresponding speech section, in particular, a major source of error in automatic recognition system of isolated words is the inaccurate detection of beginning and ending boundaries of test and reference templates, thus we must find potent method to remove the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two simple time-domain measurements - short-time energy, and short-time zero-crossing rate, which couldn't guarantee the precise results if in the low signal-to-noise ratio environments. This paper proposes a novel approach that finds the Lyapunov exponent of time-domain waveform. This proposed method has no use for obtaining the frequency-domain parameters for endpoint detection process, e.g. Mel-Scale Features, which have been introduced in other paper. Comparing with the conventional methods based on short-time energy and short-time zero-crossing rate, the novel approach based on time-domain Lyapunov Exponents(LEs) is low complexity and suitable for Digital Isolated Word Recognition System.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.117-119
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• 2006

In this work, we suggest another method to localize DFT in spatial domain. This enables DFT algorithm to be used for local pattern matching. Once calculated, it costs same load to calculate localized DFT regardless of the size or the position of local region In spatial domain. We applied this method to face detection problem and got the results which prove the utility of our method.

• The Journal of the Acoustical Society of Korea
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• v.10 no.4
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• pp.12-18
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• 1991

Detecting the fundamental frequency(Fo) of the speech signal is a problem in many speech applications. A problem of the pitch detection method in the frequency domain is occurred by the first formant and the background noise. Thus, in this paper, we proposed a pitch detection algorithm in the frequency domain that reduces the effects of the first formant and the background noise by the spectral AMDF function. Several computer simulation results showed that the proposed algorithm was very effective for fundamental frequency detection.

• Journal of Mechanical Science and Technology
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• v.15 no.2
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• pp.232-238
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• 2001

Fast Fourier Transformation is employed to convert the head variation of a pipeline in the time domain to the amplitude of the frequency domain. Applying method of characteristics to a pipeline provides a significant frequency range for a surge introduced from the valve modulation. Inverse Fast Fourier Transformation and a Finite Impulse Response Filter can be used to remove any possible noise existing from the significant frequency range of an unsteady condition. A filtered signal shows higher potential for the inverse calculation of leakage detection than the noise-added signal does. The respective performances of Inverse Fast Fourier Transformation and a Finite Impulse Response Filter are compared in terms of leakage detection capability. Characteristics of the frequency range for multiple leakages were investigated to validate the effectiveness of the noise control method in the frequency domain.

• Proceedings of the IEEK Conference
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• summer
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• pp.274-275
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• 2004

The Hough transform has been used as a tool for line detection. The main idea of the Hough transform is to transform each pixel in the image individually into the parameter domain. In this way, the Hough transform converts a difficult global detection problem in the image domain into a more easily solved local peak detection problem in the parameter domain. In this paper, we show that the discrete Hough transform is identical to the discrete Radon transform. Thus, we can use the generalized Radon transform to handle more general parameterized curve types.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.522-523
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• 2014

Analysis of faults in induction motors has become a major field of research due to importance of loss and damage reduction and maximum online performance of motors. There are several methods to analyze the faults in an induction motor from conventional Fourier transform to modern decision-making neural networks. Considering detectability of fault among all methods, a new fault detection solution has been proposed; it is called as frequency-domain Discrete Wavelet Transform (FD-DWT). In this method, the stator current is decomposed through series of low- and high-pass filters and consequently, the fault characteristics are more visible, because additional components have been reduced. The objective of this paper is early detection of input voltage unbalance in induction motor using wavelet transform in frequency domain. Experimental results show the effectiveness of the proposed method in early detection of faults.

• BioChip Journal
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• v.12 no.4
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• pp.287-293
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• 2018

Bacillus cereus can cause blood infections (i.e., sepsis). Its early detection is very important for treating patients. However, an antibody with high binding affinity to B. cereus is not currently available. Bacteriophage cell wall-binding domain (CBD) has strong and specific binding affinity to B. cereus. Here, we report the improvement in the sensitivity of an ATP bioluminescence assay for B. cereus detection using CBD-conjugated magnetic nanoparticles (CBD-MNPs). The assay was able to detect as few as 10 colony forming units (CFU) per mL and $10^3CFU\;per\;mL$ in buffer and blood. CBD-MNPs did not show any cross-reactivity with other microorganisms. These results demonstrate the feasibility of the ATP assay for the detection of B. cereus.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.157-160
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• 2002

Scene change detection is the fundamental process of automatic video indexing and retrieving. In this paper we propose a method which utilizes both compressed and uncompressed domain methods to detect scene change in a video. Candidate locations for scene change are estimated from DC images and motion vector information in compressed domain. And candidate frames are verified using edge histogram distance and color histogram distance, in uncompressed domain. The experimental results show that scene change can be detected fast and correctly by proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.22-27
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• 2012

Correct and fast detection of a micro-grid (MG) islanding is essential to the MG since operation, control and protection of the MG depend on an operating mode i.e., an interconnected mode or an islanding mode. When islanding occurs, the frequency of the point of common coupling (PCC) is not the nominal frequency during the transient state owing to the frequency rise or drop of generators in the MG. Thus, the active and reactive power calculated by the frequency domain based method such as Fourier Transform might contain some errors. This paper proposes an islanding detection algorithm for the MG based on the instantaneous active and reactive powers delivered to the dedicated line in the time domain. During the islanding mode, the instantaneous active and reactive powers delivered to the dedicated line are constants, which depend on the voltage of the PCC and the impedance of the dedicated line. In this paper, the instantaneous active and reactive powers are calculated in the time domain and used to detect islanding. The performance of the proposed algorithm is verified under various scenarios including islanding conditions, fault conditions and load variation using the PSCAD/EMTDC simulator. The results indicate that the algorithm successfully detects islanding for the MG.