• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.7
• /
• pp.884-891
• /
• 2018

In this paper, we propose an automatic earthquake P-wave detection algorithm based on the variations of the impact momentum derived from the seismic acceleration signals. The amount of change in the impact momentum induced by the acceleration refers to the influence of buildings or facilities on the earthquake, The proposed algorithm can effectively detect the seismic P-wave by simultaneously considering the amplitude and the frequency change of the seismic wave when the earthquake occurs. Computer simulations using the observed seismic signals were performed to evaluate the validity of the induced impact momentum variation and the superiority of the proposed algorithm.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.6
• /
• pp.1973-1979
• /
• 2000

Driving the need for machine vision system is growing consumer demand for quality and defect-free products. Especially it is the most important in tarpaulin's manufacturing process achieves automatically by machine vision instead of by man vision. In this paper pinholes detection is performed by using morphology algorithms. Top hat transform is one of morphology applications. This transform take high performance of defect detection in the case that unexpected changes occur in some non-uniform background. For pinholes defect, automatic visual inspection system has been developed, which was composed by a line-scan camera, illumination, a frame grabber, a motor driver and control units. This system has excellent capacity to defect pinholes to the 0.1 mm by 0.5 mm in size and to work in moving objects by maximum 20 m/min in speed.

• Journal of Power System Engineering
• /
• v.19 no.2
• /
• pp.33-39
• /
• 2015

In conducting indoor positioning by code division multiple access using spread spectrum ultrasonic waves, it is required to detect signals under the influence of near-far problem occurred by difference on signal power, caused by distance between transmitter and receiver. For discussing robustness to the problem, we verified measuring accuracy on distance from an experiment on a real space with a hardware device where our proposed method is mounted. The proposed method performs automatic signal detection by setting threshold level dynamically. As an experimental result, measurable distance were improved by the proposed method, and measurement errors were up to 50mm in distances from 1000mm to 6000mm; therefore, enough accuracy to realize self-localization or navigation for autonomous mobile robot or human was obtained.

• Journal of Biosystems Engineering
• /
• v.24 no.3
• /
• pp.253-258
• /
• 1999

This study was conducted to develop an automatic egg inspection system for detecting creaked eggs based on acoustic impulse response. This system includes a sound generator, a sound sensor with signal conditioner, and a computer. The sound generator that hit the sharp of the dull edges of an egg was constructed with a ceramic ball pendulum attached to a rotary type solenoid. The signal conditioner included a pre-amplifier and a digital signal processing (DSP) board. The parameters for distinguishing cracked and normal eggs were the area, the geometric centroid and the resonance frequency of power spectrum of the acoustic signal generated. An algorithm for on-line detection of the continuous transferring eggs was developed. The performance tests resulted with 91% success rate to separate cracked and normal eggs at the rate of 1 second per an egg.

• Proceedings of the KOSOMBE Conference
• /
• v.1994 no.12
• /
• pp.9-13
• /
• 1994

The Heat Anisotropic Diffusion Method has shown very effective for the contour detection of 2-D echocardiogram. To implement this algorithm, we have to choose the parameter C, K, and the threshold level. The choice of C and K are not very sensitive for the good edge detection of the echocardiogram, however the choice of the threshold level is very critical. Until now the threshold level is chosen by the trial and error method. In this paper, we present an automatic threshold decision method from the histogram of the gradient of boundary-like pixels.

• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.531-535
• /
• 1999

Automatic human face detection in a complex background is one of the difficult problems. In this paper, we propose an effective and robust automatic face detection approach that can locate the face region in natural scene images when the system is used as a pre-processor of a face recognition system . We use two natural and powerful visual cues, the skin color and the eyes. In the first step of the proposed system, the method based on the human skin color space by selecting flesh tone regions using normalized r-g space in color images. In the next step, we extract eye features by calculating moments and using geometrical face model. Experimental results demonstrate that the approach can efficiently detect human faces and satisfactory deal with the problems caused by bad lighting condition, skew face orientation.

• MALSORI
• /
• no.45
• /
• pp.35-45
• /
• 2003

Laryngeal diseases cause significant changes in the quality of speech production. Automatic detection of laryngeal diseases by voice is attractive because of its nonintrusive nature. In this paper, we apply speech recognition techniques to detection of laryngeal cancer, and investigate which feature parameters and classification methods are appropriate for this purpose. Linear Predictive Cepstral Coefficients (LPCC) and Mel-Frequency Cepstral Coefficients (MFCC) are examined as feature parameters, and parameters reflecting the periodicity of speech and its perturbation are also considered. As for classifier, multilayer perceptron neural networks and Gaussian Mixture Models (GMM) are employed. According to our experiments, higher order LPCC with the periodic information parameters yields the best performance.

• Journal of the Korean Institute of Telematics and Electronics D
• /
• v.34D no.7
• /
• pp.88-96
• /
• 1997

As the need of automatized system has been increased recently together with the development of industrial and military technologies, the adaptive real-time target detection technologies that can be embedded on vehicles, planes, ships, robots and so on, are hgihly demanded. Accordingly, this paper proposes a novel approach to detect and segment the moving targets using the binary phase extraction joint transform correlator (BPEJTC), the advanced image subtraction filter and convex hull processing. The BPEJTC which was used as a target detection unit mainly for target tracking compensating the camera movement. The target region has been detected by processing the successful three frames using the advanced image subtraction filter, and has become more accurate by applying the developed convex hull filter. As shown by some experimental results, it is expected that the proposed approaches for compensation of the camera movement and segmentationof of target region, can be used for th emissile guiddance, aero surveillance, automatic inspectin system as well as the target detection unit of automatic target recognition system that request adaptive real-time processing.

• The Journal of the Acoustical Society of Korea
• /
• v.18 no.1E
• /
• pp.27-31
• /
• 1999

Recent linguistic researches have brought into focus the relations between prosodic structures and syntactic, semantic or phonological structures. Most of them prove that prosodic information is available for understanding syntactic, semantic and discourse structures. But this result has not been integrated yet into recent Korean speech recognition or understanding systems. This study, as a part of integrating prosodic information into the speech recognition system, proposes an automatic detection technique of Korean accentual phrase boundaries by using one-stage DP, and the normalized pitch pattern. For making the normalized pitch pattern, this study proposes a method of modified normalization for Korean spoken language. For the experiment, this study employs 192 sentential speech data of 12 men's voice spoken in standard Korean, in which 720 accentual phrases are included, and 74.4% of the accentual phrase boundaries are correctly detected while 14.7% are the false detection rate.

• Journal of Biomedical Engineering Research
• /
• v.13 no.2
• /
• pp.115-124
• /
• 1992

An algorithm has been proposed for the automatic detection of optimal epiand endocardial left ventricular borders from 2-D short axis echocardiogram which is degraded by noise and echo drop out. For the implementation of the algorithm, we modified Ballard's Generalized Hough Transform which can be applicable only for deterministic object border, and newly proposed Fuzzy Hough Transform method. The algorithm presented here allows detection of object whose exact shapes are unknown. The algorithm only requires an approximate model of target object based on anatomical data. To detect the approximate epicardial contour of left ventricle, Fuzzy Hough Transform was applied to the echocardiogram. The optimal epicardial contour was founded by using graph searching method which contains cost function analysis process. Using this optimal epicardial contour and average thickness imformation of left ventricular wall, the approximate endocardial line was founded, and graph searching method was also used to detect optimal endocardial contour.