• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.49-62
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• 2008

This paper proposes an indoor location positioning system for the image recognition based LBS. The proposed system is a vision-based location positioning system that is implemented the augmented reality by overlaying the location results with the view of the user. For implementing, the proposed system uses the pattern matching and location model to recognize user location from images taken by a wearable mobile PC with camera. In the proposed system, the system uses the pattern matching and location model for recognizing a personal location in image sequences. The system is estimated user location by the image sequence matching and marker detection methods, and is recognized user location by using the pre-defined location model. To detect marker in image sequences, the proposed system apply to the adaptive thresholding method, and by using the location model to recognize a location, the system can be obtained more accurate and efficient results. Experimental results show that the proposed system has both quality and performance to be used as an indoor location-based services(LBS) for visitors in various environments.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.467-473
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• 2004

Caption in video plays an important role that delivers video content. Existing caption region extraction methods are difficult to extract caption region from background because they are sensitive to noise. This paper proposes the method to extract caption region in sports video using multiple frame merge and MBR(Minimum Bounding Rectangles). As preprocessing, adaptive threshold can be extracted using contrast stretching and Othu Method. Caption frame interval is extracted by multiple frame merge and caption region is efficiently extracted by median filtering, morphological dilation, region labeling, candidate character region filtering, and MBR extraction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.389-395
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• 2000

Digital Watermarking is a research area which aims at hiding secret information in digital multimedia content such as images, audio, and video. In this paper, we propose a new watermarking method with visually recognizable symbols into the digital images using wavelet transform, spread spectrum method and multilevel threshold value in considering the wavelet coefficients. The information of watermark can be extracted by subtracting wavelet coefficients with the original image and the watermarked image. The results of this experiment show that the proposed algorithm was superior to other similar watermarking algorithms. We showed Watermarking algorithm in JPEG lossy compression, resizing, LSB(Least Significant Bit) masking, and filtering.

• The Journal of the Korea Contents Association
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• v.2 no.4
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• pp.46-50
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• 2002

This paper suggests the adaptive binary method which applies advanced silt sum technique, so that threshold value can be changed heuristically according to the brightness of captured fingerprint image. Through this research, we tried to resolve threshold value setting issue by the local differences of brightness of fingerprint image in the binary image preprocessing. The experimental results show that our proposed preprocessing method demonstrates the better recognition accuracy and can be applied to minutiae extraction algorithm for fingerprint recognition system.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3185-3199
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• 1997

This paper suggests techniques to reduce coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, we choose new approximation coefficients using a non-linear approximation of luminance term. This boosts the fidelity. Our experiment employing the above methods shows enhancement in the coding time more than two times over traditional coding methods and shows improvement in PSNR value by about 1-3dB at the same com- pression rate.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.95-98
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• 2012

본 논문에서는 DCT 변환 공간상의 배경휘도와 주파수를 고려한 2차원의 개선된 광-적응 효과(luminance adaptation: LA) JND 모델을 제안한다. 기존의 LA JND 모델은 배경 휘도가 중간점인 회색에 가까울수록 JND가 낮고, 배경 휘도가 어두워지거나 밝아질수록 JND 값이 증가하는 U자형의 1차원 함수형태를 보였다. 그러나 기존 LA JND 모델은 주파수에 따른 영향이 반영되지 않았기 때문에 DCT와 같은 주파수 공간상 JND 모델로는 부정확 한 단점이 있다. 본 논문에서는 주파수와 배경휘도에 따른 2차원 LA JND 모델을 제안한다. 주파수에 따른 LA JND 값을 실제 실험을 통해 획득하였다. 실험 방법은 9가지 크기의 배경 휘도가 다르고 공간적 복잡도가 없는 균일한 영상을 대상으로 $8{\times}8$ 실수형 DCT를 수행한 다음, 15가지 경우의 주파수 크기가 다른 계수들에 대해 사람이 인지 할 때 까지 노이즈를 증가시켜서 JND 값을 찾는 방식을 사용하였다. 실험 결과 4 cpd(cycle per degree) 보다 작은 주파수 대역 에서는 기존의 LA JND 모델과 유사한 결과를 얻었지만 4 cpd보다 큰 주파수 대역에서는 오히려 배경휘도가 작은 값을 가질수록 JND가 감소하는 형태를 보였다. 수행한 실험 결과를 반영하여 주파수가 반영된 2차원 LA JND 모델을 제안한다.

• The Journal of the Acoustical Society of Korea
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• v.37 no.3
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• pp.139-146
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• 2018

Monostatic sonar systems localize targets using the time information of pulse transmission and receipt. Whereas, in asynchronous bistatic sonar systems, receivers need to detect direct blast to localize targets, since a source doesn't share pulse information with receivers. In this paper, we propose a direct blast detection algorithm, which estimates PRI (Pulse Repetition Interval) of direct blast and adaptive thresholds. Experimental results show the proposed algorithm has robust direct blast detection performance in the environment where strong background noise and target signal exist.

• The KIPS Transactions:PartC
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• v.8C no.5
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• pp.507-516
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• 2001

In this paper, we implement sequence-based anomaly detection sensor using SOM and HMM, and analyze what is important information in system call and how a threshold is decided. The new filtering and reduction rules of SOM reduces the input size of HMM. This gives real-time processing to HMM-based anomaly detection sensor. Also, we introduced an anomaly count into the sensor. Due to lessened sensibility, a user easily understand easily the detection information and false-positive was decreased. And the active coordination of the threshold value makes the detection sensor adapt according to the system condition.

• Convergence Security Journal
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• v.2 no.2
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• pp.99-108
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• 2002

In this paper, I propose a reference image updating algorithm for Intruder Detection System using a difference image method that can reliably separate moving objects from noisy background in the image sequence received from a camera at the fixed position. The proposed algorithm consists of four process determines threshold value and quantization, segmentation of a moving object area, generation of adaptive temporary image that removes a moving object area, and updates reference image using median filtering. The test results show that the proposed algorithm can generate reference image very effectively in the noisy environment.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.60-68
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• 2012

Current wireless sensor networks are considered to support more complex operations ranging from military to health care which require energy-efficient and timely transmission of large amounts of data. In this paper, we propose an adaptive temporal suppression algorithm which exploits a temporal correlation among sensor readings. The proposed scheme can significantly reduce the number of transmitted sensor readings by sensor node, and consequently decrease the energy consumption and delay. Instead of transmitting all sensor readings from sensor node to sink node, the proposed scheme is to selectively transmit some elements of sensor readings using the adaptive temporal suppression, and the sink node is able to reconstruct the original data without deteriorating data quality by linear interpolation. In our proposed scheme, sensing data stream at sensor node is divided into many small sensing windows and the transmission ratio in each window is decided by the window complexity. It is defined as the number of a fluctuation point which has greater absolute gradient than threshold value. We have been able to achieve up about 90% communication reduction while maintaining a minimal distortion ratio 6.5% in 3 samples among 4 ones.