• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.889-898
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• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• Journal of the Korea Organic Resources Recycling Association
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• v.14 no.3
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• pp.117-125
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• 2006

A microorganism capable of degrading toluene was isolated from crude oil contaminated soil and identified as Pseudomonas fluorescence. The effects of environmental factors on the degradation of toluene were investigated. The optimum temperature for toluene degradation was $30^{\circ}C$ and the maximum specific cell growth and toluene degradation rates were $0.76hr^{-1}$ and $0.36hr^{-1}$, respectively. Although the wild cells were not able to degrade toluene at $10^{\circ}C$ and $40^{\circ}C$, the cells adapted to toluene at $30^{\circ}C$ degraded 100mg/L of toluene completely at $10^{\circ}C$ and 80% of the toluene at $40^{\circ}C$. The wild cells were not able to degrade more than 200mg/L of toluene but the toluene-adapted cells degraded up to 300mg/L of toluene. Although the optimum pH was 7.0, the degradation rates were not much different in the range of 5.5 to 9.0. When nitrate was used as a nitrogen source instead of ammonium, the adaptation period became longer by 2~10 hours and the cell growth yield became lower by 45%. The toluene degradation rates after adaptation period, however, were almost same in both cases. The observations in this study will be used in the future biofilter design and operation.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.7
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• pp.418-425
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• 2015

Anaerobic Filters (AF) packed with porous ceramic floating media were operated at different operational conditions to identify the feasibility of the renewable bioenergy, methane production from swine wastewater and to verify the suitability of effluent from anaerobic filters for the subsequent biological nitrogen and phosphorus removal. Stepwise increase in organic loading rates (OLRs) or decrease in hydraulic retention times (HRTs) with influent TCOD concentration of 14,000 mg/L were utilized at mesophilic temperature. The maximum methane productivity of 1.74 volume of $CH_4$ per volume of reactor per day (v/v-d) was achieved at an hydraulic retention time (HRT) of 0.5 day (OLR 28 g TVS/L-d). Based on the biogas production, the highest total volatile solids (TVS) removal efficiency of 63% was obtained at an HRT of 3 days (OLR 4.67 g TVS/L-d), however based on the result from the effluent total chemical oxygen demand (TCOD) analysis, the highest TCOD removal efficiency of 75% was achieved. The effluent alkalinity concentration over the range of 2,050~2,980 mg/L as $CaCO_3$ at all operational conditions, could compensate the alkalinity destruction caused by nitrification. The effluent from the anaerobic filter operated under the HRT of 2 days showed the COD/TKN ratio of 15~35 and COD/TP ratio of 38~56. Therefore effluent C/N/P ratio is able to satisfy the optimum COD/TKN ratio of greater than 8.0 and COD/TP ratio of 33 for the subsequent biological nutrient removal.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2
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• pp.50-61
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• 1995

A time scale modification method yielding rate-modified speech while conserving the characteristic of speech was implemented in real-time using a goneral purpose digital signal processor. Time scale modification changed pronunciation speed only, producing a time difference between the input signal and the modified signal, making it impossible to implement it in real-time. In this thesis, a system was implemented to remove the time difference between the input and modified signals. Speech signals slowed down or speeded up by a physical time scale modification method, such as adjusting the motor speed of the cassett tape recorder, was used as the input signal. Physical modification that controled only the inter speed of the cassette tape player distorted the pitch period of the original speech. In this study, a real-time system was implemented so that the pitch-distorted speech was reconstructed back to the original by fractional sampling pitch shifting using an FIR filter, and this signal was time scale modified to match the cassette tape recorder motor speed using SOLA time-scale medification. In experiments using speech signals medifiedby the proposed method, results obtained using a 16-bit resolution ADSP2101 processor and using computer simulations employing floating point operations showed about the same average frame signal-to-noise ratio of about 20 dB.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.53-62
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• 2006

Object recognition techniques using principal component analysis are disposed to be decreased recognition rate when lighting change of image happens. The purpose of this thesis is to propose an object recognition technique using new PCA analysis method that discriminates an object in database even in the case that the variation of illumination in training images exists. And the object recognition algorithm proposed here represents more enhanced recognition rate using improved k-Nearest Neighbor. In this thesis, we proposed an object recognition algorithm which creates object space by pre-processing and being learned image using histogram equalization and median filter. By spreading histogram of test image using histogram equalization, the effect to change of illumination is reduced. This method is stronger to change of illumination than basic PCA method and normalization, and almost removes effect of illumination, therefore almost maintains constant good recognition rate. And, it compares ingredient projected test image into object space with distance of representative value and recognizes after representative value of each object in model image is made. Each model images is used in recognition unit about some continual input image using improved k-Nearest Neighbor in this thesis because existing method have many errors about distance calculation.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.575-584
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• 2008

According to the network condition, the communication network overload could be occurred when media transmitting. Many researches are being carried out to lessen the network overload, such as the filtering, load distributing, frame dropping and many other methods. Among these methods, one of effective method is frame dropping that reduces specified video frames for bandwidth diminution. B frames are dropped and then I, P frames are dropped according to dependency among the frames in frame dropping. This paper proposes a scheme for protecting copyrights by encryption, when we apply frame dropping to reduce bandwidth of media following MPEG-4 file format. We designed two kinds of frame dropping: first one stores and then sends the dropped files and the other drops frames in real-time when transmitting. We designed three kinds of encryption methods in which DES algorithm is used to encrypt MPEG-4 data: macro block encryption in I-VOP, macro block and motion vector encryption in P-VOP, and macro block and motion vector encryption in I, P-VOP. Based on these three methods, we implemented a digital right management solution for MPEG-4 data streaming. We compared the results of dropping, encryption, decryption and quality of video sequences to select an optimal method, and there is no noticeable difference between the video sequences recovered after frame dropping and the ones recovered without frame dropping. The best performance in encryption and decryption of frames was obtained when we apply the macro block and motion vector encryption in I, P-VOP.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.361-368
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• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.447-454
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• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.105-114
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• 2015

This paper proposes methods to remove background area and segment region of interest (ROI) in chest X-ray images. Conventional algorithms to improve detail or contrast of images normally utilize brightness and frequency information. If we apply such algorithms to the entire images, we cannot obtain reliable visual quality due to unnecessary information such as background area. So, we propose two effective algorithms to remove background and segment ROI from the input X-ray images. First, the background removal algorithm analyzes the histogram distribution of the input X-ray image. Next, the initial background is estimated by a proper thresholding on histogram domain, and it is removed. Finally, the body contour or background area is refined by using a popular guided filter. On the other hand, the ROI, i.e., lung segmentation algorithm first determines an initial bounding box using the lung's inherent location information. Next, the main intensity value of the lung is computed by vertical cumulative sum within the initial bounding box. Then, probable outliers are removed by using a specific labeling and the pre-determined background information. Finally, a bounding box including lung is obtained. Simulation results show that the proposed background removal and ROI segmentation algorithms outperform the previous works.

• Microbiology and Biotechnology Letters
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• v.51 no.1
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• pp.99-108
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• 2023

Several challenges arise in DNA extraction and gene amplification for airborne fungal metagenome analysis from a particulate matter (PM) samples. In this study, various conditions were tested to optimize the DNA extraction method from PM samples and polymerase chain reaction (PCR) conditions with primer set and annealing temperature. As a result of comparative evaluation of DNA extraction under various conditions, chemical cell lysis using buffer and proteinase K for 20 minutes and bead beating treatment were followed by using a commercial DNA extraction kit to efficiently extract DNA from the PM filter samples. To optimize the PCR conditions, PCR was performed using 10 primer sets for amplifying the ITS2 gene region. The concentration of the PCR amplicon was relatively high when the annealing temperature was 58℃ with the ITS3tagmix3/ITS4 primer set. Even under these conditions, when the concentration of the PCR product was low, nested PCR was performed using the primary PCR amplicon as the template DNA to amplify the ITS2 gene at a satisfactory concentration. Using the methods optimized in this study, DNA extraction and PCR were performed on 15 filter samples that collected PM2.5 in Seoul, and the ITS2 gene was successfully amplified in all samples. The optimized methods can be used for research on analyzing and interpreting the fungal metagenome of atmospheric PM samples.