• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1586-1592
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• 1999

In DWMT, CMFB is employed in the synthesis/analysis part. The CMFB uses filters of greater length than the DFT, resulting in reduced interference between the carriers. In addition, the CMFB system is computationally efficient and fast algorithms are available for their implementation. Traditional designs for the prototype filters of CMFB usually involve nonlinear optimizations. Thus the required design time is considerably large even for small filter orders. In this paper, a prototype filter design method for CMFB is presented using optimal window method. The design process is reduced to the optimization of a single parameter and consequently the required design time is much less than those of the existing methods. It is shown that the stopband performance of the proposed method is better than that of the Kaiser window method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.380-388
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• 2019

Jet engine modulation(JEM) signals are widely used for target recognition. These signals coming from a potentially hostile aircraft provide specific information about the jet engine. In order to obtain the number of blades, which is uniquely provided by the JEM signal, one must extract the spool rate, which is the rotation speed of the blades. In this paper, we propose an algorithm to extract the spool rate from a weak JEM signal. A criterion is developed to extract the spool rate from the JEM signal by analyzing the intensity of the JEM signal component. The weak signal is first subjected to a high-pass filtering-based process, which modifies it to facilitate spool rate extraction. We then apply a peak detection process and extract the spool rate. The technique is simpler than the existing CEMD or WD method, is accurate, and greatly reduces the time required.

• Journal of Korean Tunnelling and Underground Space Association
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• v.15 no.3
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• pp.187-199
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• 2013

Umbrella arch method (UAM) used for improving the stability of the tunnel ground condition has been widely applied in the tunnel construction projects due to the advantage of obtaining both reinforcement and waterproof. The purpose of this study is to develop the evaluation technique of the integrity of bore-hole in UAM by using a non-destructive test and to evaluate the possibility of being applied to the field. In order to investigate the variations of frequency depending on grouted length, the specimens with different grouted ratios are made in the two constraint conditions (free boundary condition and embedded condition). The hammer impact reflection method in which excitation and reception occur simultaneously at the head of pipe was used. The guided waves generated by hitting a pipe with a hammer were reflected at the tip and returned to the head, and the signals were received by an acoustic emission (AE) sensor installed at the head. For the laboratory experiments, the specimens were prepared with different grouted ratios (25 %, 50 %, 75 %, 100 %). In addition, field tests were performed for the application of the evaluation technique. Fast Fourier transform and wavelet transform were applied to analyze the measured waves. The experimental studies show that grouted ratio has little effects on the velocities of guided waves. Main frequencies of reflected waves tend to decrease with an increase in the grouted length in the time-frequency domain. This study suggests that the non-destructive tests using guided ultrasonic waves be effective to evaluate the bore-hole integrity of the UAM in the field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.126-133
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• 2003

This paper is related to a morphological segmentation method for extracting the moving object in video sequence using global motion compensation and two-dimensional spatio-temporal entropic thresholding. First, global motion compensation is performed with camera panning vector estimated in the hierarchical pyramid structure constructed by wavelet transform. Secondly, the regions with high possibility to include the moving object between two consecutive frames are extracted block by block from the global motion compensated image using two-dimensional spatio-temporal entropic thresholding. Afterwards, the LUT classifying each block into one among changed block, uncertain block, stationary block according to the results classified by two-dimensional spatio-temporal entropic thresholding is made out. Next, by adaptively selecting the initial search layer and the search range referring to the LUT, the proposed HBMA can effectively carry out fast motion estimation and extract object-included region in the hierarchical pyramid structure. Finally, after we define the thresholded gradient image in the object-included region, and apply the morphological segmentation method to the object-included region pixel by pixel and extract the moving object included in video sequence. As shown in the results of computer simulation, the proposed method provides relatively good segmentation results for moving object and specially comes up with reasonable segmentation results in the edge areas with lower contrast.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.282-294
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• 2017

In this paper, we propose a novel intelligent headlight control (IHC) system which is durable to various road lights and camera movement caused by vehicle driving. For detecting candidate light blobs, the region of interest (ROI) is decided as front ROI (FROI) and back ROI (BROI) by considering the camera geometry based on perspective range estimation model. Then, light blobs such as headlights, taillights of vehicles, reflection light as well as the surrounding road lighting are segmented using two different adaptive thresholding. From the number of segmented blobs, taillights are first detected using the redness checking and random forest classifier based on Haar-like feature. For the headlight and taillight classification, we use the random forest instead of popular support vector machine or convolutional neural networks for supporting fast learning and testing in real-life applications. Pairing is performed by using the predefined geometric rules, such as vertical coordinate similarity and association check between blobs. The proposed algorithm was successfully applied to various driving sequences in night-time, and the results show that the performance of the proposed algorithms is better than that of recent related works.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1069-1077
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• 2008

The railway abrasion measurement system have to satisfy two conditions to increase the measurement accuracy as follows. The laser region which is projected on the rail have to be extracted without the geometrical distortion. The mapping of the acquired laser region data on the rail profile have to be processed exactly. But, the conventional railway abrasion measurement system is deeply effected by the foreign substance( dust, rainwater, and so on ) on the railway or the sensitive response characteristic of the laser to the external measurement circumstance, and then the measurement errors arise from above factors. When the laser region is projected on the rail extracts from the acquired image, the interference of the light with the same frequency as the laser system occurs the serious problems. In the process of the mapping between the railway profile and the extracted laser region, the measurement accuracy is very highly effected by the geometrical distortion and the abnormal variation. In this Paper, we propose the novel method to increase the accuracy of the railway abrasion measurement dramatically. we designed and manufactured the high precision and fast image processing board with DSP Core and FPGA to measure the railway abrasion. The image processing board has the capability that the image of 1024X1280 from camera can be processed with the speed of 480 frame/sec. And, we apply the image processing algorithm base on the wavelet to extract the laser region is projected on the rail exactly. Finally, we developed high precision railway abrasion measurement system with the error range less than +/-0.5mm by which 2D image data is covered 3D data and mapped on the rail profile using the camera model and the perspective transform.