• Journal of the Korean Society of Tobacco Science
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• v.21 no.2
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• pp.136-143
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• 1999

This study was conducted to evaluate the degradation characteristics of waste cigarette filters under 0, 5, 10, and 15cm in depth from soil surface by environmental conditions. Weather was the most important factor during degradation of waste cigarette filters in this study. Bulking of cellulose acetate filaments exposed on soil surface was observed after 2 months, but the form of filter was kept up after 12 months. The treated cigarette filters in soil landfill revealed a little different degradation pattern at each soil landfill depth, The sample in 5cm depth of soil was more degraded then other site. A fluffy appearance of cellulose acetate filaments in the control filter rods was also developed more strongly in soil landfill then on soil surface. From the observation of waste cigarette filters by scanning electron microscopy, much degradation of the fiber of waste cigarette filters could be ascertained in soil landfill. The weight of waste cigarette filters under 5cm from soil surface was reduced about 50%, and the tensile strength of the samples in soil surface and under 5cm from soil surface were reduced 66.0% and 92.4%, respectively. The microbial experiment date that the viable cell number in microbial population and cellulolytic microorganisms showed the maximum values under 5cm from soil surface, suggest that microorganisms in soil play an important roll in the degradation of acetate cigarette filters.

• Journal of IKEEE
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• v.14 no.4
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• pp.312-316
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• 2010

We describe in this paper how to facilitate ad hoc routing with a particle filter in a hostile radio environment for multi-hop wireless ad hoc networks that connect multi-robots. The proposed scheme increases a connection's throughput by exploiting alternative links without going through the procedure of route discovery when link failure happens among multi-robots' networking. The scheme is implemented by using a particle filter to find strongly connected nodes. The filter estimates the probability distribution function in a sample-based manner with N particles. The particles are associated with a weight which represents the probability of the corresponding node to be the node with the best link. At every step of the estimation, the weights of particles are calculated and particles are resampled based on the weights. Since a node with the strongest link status possesses the largest number of particles, we take this node to forward the packets.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.259-264
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• 2006

It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. The conventional way of determining Q and R requires good a priori knowledge of the process noises and measurement errors, which normally comes from intensive empirical analysis. Many adaptive methods have been developed to overcome the conventional Kalman filter's limitations. Starting from covariance matching principles, an innovative adaptive process noise scaling algorithm has been proposed in this paper. Without artificial or empirical parameters to be set, the proposed adaptive mechanism drives the filter autonomously to the optimal mode. The proposed algorithm has been tested using road test data, showing significant improvements to filtering performance.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.25-32
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• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.25-32
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• 2016

In this paper, we propose a method that is tracking an object in real time using particle filter and the observation model with edge. First of all, the proposed method defines the object to be tracked in the initial frame. Then, it generates the edge observation model for the object to be tracked and a set of particles. It calculates the weight by comparing the average of the middle distance in eight-way of particle filter edge model with that in edge observation model, and then updates the weight with the calculated value. After resampling particles using the updated weights, it estimates the current location of the tracked object. Finally, this paper demonstrates the performance of the stable tracking through comparison with the existing method by using a number of experimental data.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.22-27
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• 2014

Blocking and ringing artifacts continue to be the most serious defects that occur in images and video streams compressed to low bit rates using block-based discrete cosine transform(DCT) compression standards. These artifacts contain the high frequency components near the block and the edge boundaries. Usually the lowpass filter can remove them. However, simple lowpass filter results into blur by removing important information such as edges at the same time. To overcome these problems, we propose a novel postfiltering algorithm that calculate the weight value based on the intensity similarity in the neighboring pixels and multiply this weight to the Gaussian lowpass filter coefficient. Experimental results show that the proposed technique provides satisfactory performance in both objective and subjective image quality.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.2
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• pp.71-76
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• 2016

Digital image processing is being utilized in various fields including medical industry, satellite photos, and factory automation image recognition. However, this kind of image data produces heat by an external cause in the course of being processed, transmitted, and stored. Most typical noises added in the images are AWGN and salt and pepper. MF, CWMF, and AWMF are methods used to restore images damaged by AWGN and the existing methods are likely to damage detailed information such as an edge. Therefore, this paper suggests an algorithm applying weight of average filter, average filter depending on pixel, and spatial weight filter based on edge size of local mask in an AWGN environment, in a different way. Also, this paper compares functions of existing methods by using PSNR to prove excellence of the suggested algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.317-325
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• 2016

This paper describes the technique for Radar Particle filter for TBD(Track Before Detect) processing. TBD technique is applied when target is difficult to detect due to low signal-to-noise ratio caused by strong clutter environments, small RCS targets and stealth targets. Particle filter is suitable for a recursive TBD algorithm and has improved estimation accuracy than Kalman filter. In this paper, we will present a new method of calculating particle weight, when observation values(including strong clutter) are received at the same time. Estimation error performance of the particle filter algorithm is analyzed by using the virtual radar observation scenario.

• Journal of the Korean Society for Railway
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• v.9 no.6 s.37
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• pp.761-765
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• 2006

At present, harmonic currents cause serious problems in power conversion system using the semiconductor switching device. Also some of the conversion system provokes harmonic currents against to the main power supply system and causes hindrances for the system. Main power impedance of the traditional LC passive filter method, influences on the filter characteristics and amplifies the harmonics when resonance phenomenon is occurred. And the traditional existing 2 level inverter systems show the limit in capacity of voltage and current in case of occurring sudden load change. So, to solve this problem active filter which uses cascaded H-bridge multi level inverter has been designed and ex-filter system circuits were totally investigated. With multi level active filtering system not only the size of filter but also the size of filter for transformer can be reduced by half and so as to the weight, while the capacity of inverter can be double sized and wave forms can be compensated exactly and precisely. Also by the benefit of the increase in rating capacity, the various currents owing to the load fluctuation can be dealt more steadily. In order to simulate the wave form of harmonics based on the measured data on the AC 25kV high speed Domestic Commercial railway, it was simulated with PSCAD/EMTDC and PSIM. Based on the results of this demonstration, the power supply system and inverter system would be more stable and also promoting its efficiency.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.56-63
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• 2012

In this paper, adaptive unsharp masking using bilateral filter, edge-preserving smoothing filter is proposed to reduce the overshoot and jagging artifact in sharpening images. Previous image enhancement methods including unsharp masking(UM) can emphasize high-frequency details strongly, but often cause several artifacts such as overshooting, noise, jagging and so on. Proposed image enhancement method preserves edges well because of using bilateral filter and sensitively controls a weight according to edge's directions. Therefore, it enhances sharpness and effectively reduces overshoot and jagging artifacts. Simulation results comparing output of previous AUM with proposed method show that proposed algorithm makes images properly enhanced, and we know that overshoot and jagging artifacts are many reduced.