• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1171-1179
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• 2021

Image forensic is performed to check image limpidness. In this paper, a robust scheme is discussed to detect median filtering in low quality images. Detection of median filtering assists in overall image forensic. Improved spatial statistical features are extracted from the image to classify pristine and median filtered images. Image array data is rescaled to enhance the spatial statistical information. Features are extracted using Markov model on enhanced spatial statistics. Multiple difference arrays are considered in different directions for robust feature set. Further, texture operator features are combined to increase the detection accuracy and SVM binary classifier is applied to train the classification model. Experimental results are promising for images of low quality JPEG compression.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.143-151
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• 2012

A new data-driven method for the design of a blind modulation frequency filter that suppresses the slow-varying noise components is proposed. The proposed method is based on the temporal local decorrelation of the feature vector sequence, and is done on an utterance-by-utterance basis. Although the conventional modulation frequency filtering approaches the same form regardless of the task and environment conditions, the proposed method can provide an adaptive modulation frequency filter that outperforms conventional methods for each utterance. In addition, the method ultimately performs channel normalization in a feature domain with applications to log-spectral parameters. The performance was evaluated by speaker-independent isolated-word recognition experiments under additive noise environments. The proposed method achieved outstanding improvement for speech recognition in environments with significant noise and was also effective in a range of feature representations.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2301-2306
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• 2005

Even if there are lots of researches on localization using 2D range finder in static environment, very few researches have been reported for robust real-time localization of mobile robot in uncertain and dynamic environment. In this paper, we present a new localization method based on ICP(Iterative Closest Point) algorithm for navigation of mobile robot under dynamic or uncertain environment. The ICP method is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. We use the method to align global map with 2D scanned data from range finder. The proposed algorithm accelerates the processing time by uniformly sampling the line fitted data from world map of mobile robot. A data filtering method is also used for threshold of occluded data from the range finder sensor. The effectiveness of the proposed method has been demonstrated through computer simulation and experiment in an office environment.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.70-72
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• 2009

In this paper, nonlinear active noise control(ANC) of a 3rd-order Volterra system, which is robust to background noise variation, is proposed along with a variable step-size Gauss-Seidel pseudo affine projection(VSSGS-PAP) algorithm. Simulation results demonstrate that the proposed approach yields better nonlinear ANC performance in a background noise variation environment, compared with the conventional methods for the nonlinear ANC.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1034-1039
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• 1992

Time Delay Controller(TDC) is a model following controller which uses input and output values and state variables to estimate additional quantity of dynamics due to external disturbances and/or model parameters variation at some past instant. TDC is very robust against parametric uncertainty whil it is not robust against unmodeled dynamics even showing instability. To solve this problem a stability anlysis is performed and a compensation technique using reduced order observer, Anti-Filtering Compensator(AFC), is proposed for a case in which the high order kinown dynamics is deliberately ignored. If the ignored dynamics causes instability of the TDC control system, AFC is shown to be indispensible fot a stable implementation of TDC.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.255-261
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• 2000

This paper presents the results of the robust H(sub)$\infty$ FIR filtering for a class of nonlinear continuous time-varying systems subject to real norm-bounded parameter uncertainty and know Lipschitz nonlinearity under sampled measurements. We address the problem of designing filters, using sampled measurements, which guarantee a prescribed H(sub)$\infty$ performance in continuous time-varying context, irrespective of the parameter uncertainty and unknown initial states. The infinite horizon causal H(sub)$\infty$FIR filter are investigated using the finite moving horizon in terms of two Riccati equations with finite discrete jumps.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2001.11a
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• pp.464-468
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• 2001

In this paper, we propose a robust watermarking technique that accepts time scaling, pitch shift, add noise and a lot of lossy compression such as MP3, AAC, WMA. The technique is developed based on digital filtering. Being designed according to critical band of HAS (human auditory system), the digital filters nearly affect audio quality. Furthermore, before implementing digital filtering, wavelet transform decomposes the audio signal into several signals that is composed of specific frequencies. Designed digital filters scan the decomposed signal. The designed digital filter, band-stop filter, distorts and eliminates specific frequencies of audio signals. Watermarking detection can be accomplished by FFT (Fast Fourier Transform). Firstly, segments of audio signal are transformed by FFT. Then, the obtained amplitude spectrum by FFT is summed repeatedly. Finally the watermark detector can find filters used to watermark encoding based on eliminating frequencies. The suggested technique can embed 4bits/s in a robust manner.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.93-96
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• 2002

This paper presents robust and efficient scene-based video watermarking method using visual rhythm (spatio-temporal slice) in compressed domain. Scene change can be detected easily using visual rhythm and video sequences are conveniently edited at the scene boundaries. Therefore, scene-based watermark embedding Process it a natural choice. Temporal spread spectrum can be achieved by applying spread spectrum methods to visual rhythm. Additive Gaussian noise, low-pass filtering, median filtering and histogram equalization attack are simulated for all frames. Frame sub-sampling is also simulated as a typical video attack Simulation results show that proposed algorithm is robust and efficient in the presence of such kind of attacks.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.122-129
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• 2016

There have been a lot of researches on object recognition in computer vision. The SURF(Speeded Up Robust Features) algorithm based on feature detection is faster and more accurate than others. However, this algorithm has a shortcoming of making an error due to feature point mismatching when extracting feature points. In order to increase a success rate of object recognition, we have created an object recognition system based on SURF and RANSAC(Random Sample Consensus) algorithm and proposed the pattern recognition filtering. We have also presented experiment results relating to enhanced the success rate of object recognition.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.1
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• pp.18-26
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• 2008

The invariance relation existing in the non-negative matrix factorization (NMF) is used for constructing robust image hashes in this work. The image is first re-scaled to a fixed size. Low-pass filtering is performed on the luminance component of the re-sized image to produce a normalized matrix. Entries in the normalized matrix are pseudo-randomly re-arranged under the control of a secret key to generate a secondary image. Non-negative matrix factorization is then performed on the secondary image. As the relation between most pairs of adjacent entries in the NMF's coefficient matrix is basically invariant to ordinary image processing, a coarse quantization scheme is devised to compress the extracted features contained in the coefficient matrix. The obtained binary elements are used to form the image hash after being scrambled based on another key. Similarity between hashes is measured by the Hamming distance. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as Gaussian filtering, moderate noise contamination, JPEG compression, re-scaling, and watermark embedding. Hashes of different images have very low collision probability. Tampering to local image areas can be detected by comparing the Hamming distance with a predetermined threshold, indicating the usefulness of the technique in digital forensics.