• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.840-855
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• 2011

In the context of additive noise steganography model, we propose a method to detect least significant bit (LSB) matching steganography in grayscale images. Images are decomposed into detail sub-bands with local linear transform (LLT) masks which are sensitive to embedding. Novel normalized characteristic function features weighted by a bank of band-pass filters are extracted from the detail sub-bands. A suboptimal feature set is searched by using a threshold selection algorithm. Extensive experiments are performed on four diverse uncompressed image databases. In comparison with other well-known feature sets, the proposed feature set performs the best under most circumstances.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.315-322
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• 2006

In the application rising IP multicast, the waste of available bandwidth occurs of reducing of transmission rate in non-congestion local caused by reducing of transmission rate in congestion local. In this paper, to solve such a problem, we propose a dynamic multicast method using IP multicast and overlay multicast. In proposed method, we elected a local representative for overlay multicasting. When the transmission rate of a group is less than transmission rate threshold, the representative can transmits duplicative packets. In simulation results, it was known that proposed method uses bandwidth more efficiently.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.333-336
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• 2002

This paper presents a new image segmentation method using fuzzy measures which reflect the local property of an image as well as the global property of an image An image is globally segmented into the crisp region and the ambiguous region in terms of the Index of fuzziness measured over all pixels of an image. The ambiguous region is luther partitioned into background and object in terms of the index of fuzziness computed over the set of neighboring pixels reflecting the local property most. From the experimental results, this method shows the effective ambiguity handling capability in segmenting an image.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1649-1657
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• 2008

In this paper, to overcome the failure of binarization for the characters suffered from low contrast and non-uniform illumination in license plate character recognition system, we improved the binarization method by combining local thresholding with global thresholding and edge detection. Firstly, apply the local thresholding method to locate the characters in the license plate image and then get the threshold value for the character based on edge detector. This method solves the problem of local low contrast and non-uniform illumination. Finally, back-propagation Neural Network is selected as a powerful tool to perform the recognition process. The results of the experiments i1lustrate that the proposed binarization method works well and the selected classifier saves the processing time. Besides, the character recognition system performed better recognition accuracy 95.7%, and the recognition speed is controlled within 0.3 seconds.

• Journal of the Korean Institute of Telematics and Electronics
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• v.12 no.1
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• pp.1-6
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• 1975

The boundary has been one of the most important information in radiographic images and the degrees of difficulty involved varies greatly with the quality of the picture. These Buantifications are the means to diagnoses. The purpose of this paper is to quantify intensity variation and the threshold decision which is based on statistical principles and is developed to detect limits in liver scintigrams the entire picture is devide4 into 64 small regions. The kurtosis and variances for each smal region are used as indications to select the histograms the thresholds are computed according to the method o(maximum likelihood which minimizes the probability o( misclassification. Therefore Ive have demonstrated the applicability of the boundary detection and proved good agreement with human recognition, and we can use it for the diagnosis data of liver disease.

• Journal of the Korean Academy of Clinical Electrophysiology
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• v.4 no.1
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• pp.63-83
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• 2006

This study conducted the following experiment to examine anesthetic effects of 500 kHz ultrasound with lidocaine. Clinical experiment was conducted to compare local anesthetic effects by ultrasound frequencies and drugs with 40 normal adults and it divided subjects into experimental group (I) applying only ultrasound, ointment group (II) applying only lidocaine, phonophoresis group of 1 MHz (III), phonophoresis group of 500 kHz lidocaine (IV) for pain threshold and nerve conduct experiments. Mechanical threshold was measured with von Frey monofilament, thermal pain threshold with halogen lamp and digital thermometer, action potential in median nerve with diagnostic electromyography before and after treatment, and at 30 min., 60 min., 90 min., and 120 min. after treatment. Results of this study can be summarized as follows. Topical anesthesia experiment showed that pain threshold of phonophoresis groups was significantly increased, but there were little differences in ultrasound frequency and drugs among phonophoresis groups. Conduction anesthesia experiment showed that phonophoresis group of 500 kHz using lidocaine had significant difference in pain threshold and sensory nerve conduction compared to ointment group and ultrasound group, but there was no great difference from other phonophresis groups and light nerve block effect was found. It was considered that application of 500 kHz ultrasound using lidocaine will be more effective in deep anesthesia or nerve block than 1 MHz ultrasound. However, researches considering various frequencies, intensities and application hours in low frequency areas including kHz ultrasound are needed to increase deep permeation of drugs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12B
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• pp.1083-1096
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• 2008

This paper proposes an energy-aware path management scheme, so-called the TBP(Threshold based Back-Pressure) algorithm, which is designed for lifetime extension of the energy-constrained wireless sensor networks. With the goal of fair energy consumptions, we extensively utilize the available paths between the source and the sink nodes. The traffic distribution feature of the TBP algorithm operates in two scales; the local and the whole routing area. The threshold and the back-pressure signal are introduced for implementing those operations. It is noticeable that the TBP algorithm maintains the scalability by defining both the threshold and the back-pressure signal to have their meanings locally confined to one hop only. Throughout several experiments, we observe that the TBP algorithm enhances the network-wide energy distribution. which implies the extension of the network lifetime. Additionally, both the delay and the throughput outcomes show remarkable improvements. This shows that the energy-aware path control scheme holds the effects of the congestion control.

• Progress in Superconductivity
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• v.5 no.1
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• pp.26-30
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• 2003

Magneto-cardiogram(MCG) signals may be highly distorted by the environmental noise, such as power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. Several kinds of digital filters and noise cancellation methods have been designed and realized by many researchers, but these methods gave some problems that the original signal may be distorted by digital filter due to the wideband characteristics of background noise. To eliminate noise effectively without distortion of MCG signals, we performed multi-level frequency decomposition using wavelet packets and local adaptive noise cancellation in each local frequency range. In addition to the proposed wavelet filter to eliminate these various non-stationary noise elements, the local adaptive filter using the least mean square(LMS) algorithm and the soft threshold do-noising method are introduced in this paper. The signal to noise ratio(SNR) and the reconstruction square error(RSE) are calculated to evaluate the performance of the proposed method and compared with the results of the conventional wavelet filter and adaptive filter. The experimental results show that the proposed local adaptive filtering method is better than the conventional methods.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.223-230
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• 2006

A window-based image processing is an elementary part of image processing area. Because window-based image processing is computationally intensive and data intensive, it is hard to perform ail of the operations of a window-based image processing in real-time by using a software program on general-purpose computers. This paper proposes a parallel hardware architecture that can perform a window-based image processing in real-time using FPGA(Field Programmable Gate Array). A dynamic threshold circuit and a local histogram equalization circuit of the proposed architecture are designed using VHDL(VHSIC Hardware Description Language) and implemented with an FPGA. The performances of both implementations are measured.

• The Journal of the Acoustical Society of Korea
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• v.34 no.4
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• pp.321-327
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• 2015

In this paper, we propose an algorithm for achieving robust Visual Voice Activity Detection (VVAD) for enhanced speech recognition. In conventional VVAD algorithms, the motion of lip region is found by applying an optical flow or Chaos inspired measures for detecting visual speech frames. The optical flow-based VVAD is difficult to be adopted to driving scenarios due to its computational complexity. While invariant to illumination changes, Chaos theory based VVAD method is sensitive to motion translations caused by driver's head movements. The proposed Local Variance Histogram (LVH) is robust to the pixel intensity changes from both illumination change and translation change. Hence, for improved performance in environmental changes, we adopt the novel threshold estimation using total variance change. In the experimental results, the proposed VVAD algorithm achieves robustness in various driving situations.