• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.491-496
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• 2003

We present a new watermark design tool for digital images and digital videos that are based on human visual system (HVS) characteristics. In this tool, basic mechanisms (inhibitory and excitatory behaviour of cells) of HVS are used to determine image dependent upper bound values on watermark insertion. This allows us to insert maximai allowable transparent watermark, which in turn is extremely hard to attack with common image processing, Motion Picture Experts Group (MPEG) compression. As the number of details (e.g. edges) increases in an image, the HVS decrease its sensitivity to the details. In the same manner, as the number of motion increases in a video signal, the HVS decrease its sensitivity to the motions. We model this decreased sensitivity to the details and motions as an (motion) entropy masking. Entropy masking model can be efficiently used to increase the robustness of image and video watermarks. We have shown that our entropy-masking model provides watermark scheme with increased transparency and henceforth increased robustness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2677-2684
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• 2009

In this paper, we study a watermarking method based on the informed coding and embedding by means of trellis code and entropy masking. An image is divided as $8{\times}8$ block with no overlapping and the discrete cosine transform(DCT) is applied to each block. Then the 16 medium-frequency AC terms of each block are extracted. Next it is compared with gaussian random vectors having zero mean and unit variance. As these processing, the embedding vectors with minimum value of linear combination between linear correlation and Watson distance can be obtained by Viterbi algorithm at each stage of trellis coding. For considering the image characteristics, we apply different weight value between the linear correlation and the Watson distance using the entropy masking. To evaluate the performance of proposed method, the average bit error rate of watermark message is calculated from different several images. By the experiments the proposed method is improved in terms of the average bit error rate.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.351-357
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• 2019

UAV (Unmanned Aerial Vehicle) images can be exploited for rapid forest fire damage assessment by virtue of UAV systems' advantages. In 2019, catastrophic forest fire occurred in Goseong and Sokcho, Korea and burned 1,757 hectares of forests. We visited the town in Goseong where suffered the most severe damage and conducted UAV flights for forest fire damage assessment. In this study, economic and rapid damage assessment method for forest fire has been proposed using UAV systems equipped with only a RGB sensor. First, forest masking was performed using automatic elevation thresholding to extract forest area. Then ExG (Excess Green) vegetation index which can be calculated without near-infrared band was adopted to extract damaged forests. In addition, entropy filtering was applied to ExG for better differentiation between damaged and non-damaged forest. We could confirm that the proposed forest masking can screen out non-forest land covers such as bare soil, agriculture lands, and artificial objects. In addition, entropy filtering enhanced the ExG homogeneity difference between damaged and non-damaged forests. The automatically detected damaged forests of the proposed method showed high accuracy of 87%.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.344-344
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• 2004

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.167-175
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• 2021

Semi-supervised learning uses both labeled data and unlabeled data. Recently consistency regularization is very popular in semi-supervised learning. Unsupervised data augmentation (UDA) that uses unlabeled data augmentation is also based on the consistency regularization. The Kullback-Leibler divergence is used for the loss of unlabeled data and cross-entropy for the loss of labeled data through UDA learning. UDA uses techniques such as training signal annealing (TSA) and confidence-based masking to promote performance. In this study, we propose to use Jensen-Shannon divergence instead of Kullback-Leibler divergence, reverse-TSA and not to use confidence-based masking for performance improvement. Through experiment, we show that the proposed technique yields better performance than those of UDA.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.33-41
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• 2001

Currently, the compression is one of the most important technology in multimedia society. Audio files arc rapidly propagated throughout internet Among them, the most famous one is MP-3(MPEC-1 Laver3) which can obtain CD tone from 128Kbps, but tone quality is abruptly down below 64Kbps. MPEC-II AAC(Advanccd Audio Coding) is not compatible with MPEG 1, but it has high compression of 1.4 times than MP 3, has max. 7.1 and 96KHz sampling rate. In this paper, we propose an algorithm that decreased the capacity of AAC encoding computation but increased the processing speed by optimizing psychoacoustic model which has enormous amount of computation in MPEG 2 AAC encoder. The optimized psychoacoustic model algorithm was implemented by C++ language. The experiment shows that the psychoacoustic model carries out FFT(Fast Fourier Transform) computation of 3048 point with 44.1 KHz sampling rate for SMR(Signal to Masking Ratio), and each entropy value is inputted to the subband filters for the control of encoder block. The proposed psychoacoustic model is operated with high speed because of optimization of unpredictable value. Also, when we transform unpredictable value into a tonality index, the speed of operation process is increased by a tonality index optimized in high frequency range.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.4
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• pp.318-327
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• 2012

The operating sound radiated from a laser printer includes tonal noise components caused by the rotating mechanical parts such as gear, shaft, motor, fan, etc. The negative effects of the tonal noise components need to be considered in the process of developing a sound quality index for the quantitative evaluation of the emotional satisfaction in terms of psycho-acoustics. However, in a previous paper, it was confirmed that the Aures tonality did not have enough correlation with the results of jury evaluation. The sound quality index based on loudness, articulation index, fluctuation strength has a little problem in considering the effects of rotating mechanical parts on the sound quality. In this paper, to solve the tonality evaluation problem, the calculation algorithm of Aures tonality was investigated in detail to find the cause of decreasing the correlation. The new tonality evaluation model was proposed by modifying and optimizing the masking effect, loudness ratio, and shape of weighting curve based on the basic algorithm of Aures tonality, and applied to two kinds of operating sound groups in order to verify the usefulness of proposed model. As a result, it is confirmed that the proposed tonality evaluation model has enough correlation and usefulness for expressing the tonalness in the operating sounds of laser printers. In the following paper, this results will be used to model the sound quality index as the input data by using the classification algorithm.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.179-187
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• 2008

In this paper, we apply a set of algorithms to classily normal and cancer nucleus from uterine cervical pap-smear images. First, we use lightening compensation algorithm to restore color images that have defamation through the process of obtaining $1{\times}400$ microscope magnification. Then, we remove the background from images with the histogram distributions of RGB regions. We extract nucleus areas from candidates by applying histogram brightness, Kapur method, and our own 8-direction contour tracing algorithm. Various binarization, cumulative entropy, masking algorithms are used in that process. Then, we are able to recognize normal and cancer nucleus from those areas by using three morphological features - directional information, the size of nucleus, and area ratio - with fuzzy membership functions and deciding rules we devised. The experimental result shows our method has low false recognition rate.