• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.450-456
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• 2016

STDR (sequence time domain reflectometry) to detect a cable fault using a pseudo noise sequence as a reference signal, and time correlation analysis between the reference signal and reflection signal is robust to noisy environments and can detect intermittent faults including open faults and short circuits. On the other hand, if the distance of the fault location is far away or the fault type is a soft fault, attenuation of the reflected signal becomes larger; hence the correlation coefficient in the STDR becomes smaller, which makes fault detection difficult and the measurement error larger. In addition, automation of the fault location by detection of phase and peak value becomes difficult. Therefore, to improve the cable fault detection of a conventional STDR, this paper proposes the algorithm in that the peak value of the correlation coefficient of the reference signal is detected, and a peak value of the correlation coefficient of the reflected signal is then detected after removing the reference signal. The performance of the proposed method was validated experimentally in low-voltage power cables. The performance evaluation showed that the proposed method can identify whether a fault occurred more accurately and can track the fault locations better than conventional STDR despite the signal attenuation. In addition, there was no error of an automatic fault type and its location by the detection of the phase and peak value through the elimination of the reference signal and normalization of the correlation coefficient.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.470-477
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• 2013

The aim of this study is to suggest a detection method of water surface location and its evaluation results of application for same vertical position in two successive images with time interval including both staff gauge and water surface. A specific rectangular inspection area is defined from the top of watermark and then the correlation coefficients for the inspection area of the same position of two images with short time interval is calculated. Accordingly, it is possible to identify differences between changing area and fixed area of pixel density by the water flow. The photographs taken in the laboratory were analyzed in order to validate the proposed technique. As the result of the experiment, it is identified that characteristic of correlation coefficients depends on the size of the inspection area. In the case that the inspection area is within the entire width of the watermark, water surface characteristic according to correlation coefficients is clearly noticeable. Thus, it is identified that the proposed technique can be utilized to search water surfaces. Besides, using corelation analysis of two images with time interval, it is identified that error range between 10 and 42cm was reduced in the level of 2.6cm or less in the contaminated photo of existing image stage gauge. Therefore, it is expected that the suggested method can be utilized to enhance image stage gauge performance improving the previous water surface detection method.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.60-67
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• 2007

The spectrum sensing is important for decision of using frequency band. It checks the frequency band for cognitive radio system. In this paper, we apply autocorrelation function to the energy detection method. We use the autocorrelation function to improve the performance of spectrum sensing method based on the energy detection method. This method is different from cyclostationary process method where parameters such as the mean or the autocorrelation function are time-varying periodically. And we propose improved method that is robust in poor radio environment. If the proposed method applies for sensing in the cognitive radio system, it will have the structural simplicity and the fast computation of spectrum sensing.

• ALGAE
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• v.28 no.3
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• pp.289-296
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• 2013

For the quantitative detection of algal toxin, microcystin, a chemiluminescence immunochromatographic assay method was developed. The developed system consists of four parts, chemiluminescence assay strip (nitrocellulose membrane), horse radish peroxidase labeled microcystin monoclonal antibodies, chemiluminescence substrate (luminol and hydrogen peroxide), and luminometer. The performance of the chemiluminescence immunochromatographic assay system was compared with high performance liquid chromatography (HPLC) detection. The detection limit of chemiluminescence immunochromatographic assay system is several orders of magnitude lower than with HPLC. The chemiluminescence immunochromatography and HPLC results correlated very well with the correlation coefficient ($r^2$) of 0.979.

• Proceedings of the IEEK Conference
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• summer
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• pp.442-446
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• 2004

This paper propose scene change detection algorithm using coefficient of forward prediction macro-block, backward prediction macro-block, and intra-coded macro-block on getting motion estimation. Proposed method detect scene change with correlation according picture type forward two picture or forward and backward two picture on video sequences. Proposed algorithm is high accuracy and can detect all scene change on video, and detect to occur scene change on P, B, I-picture.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.151-159
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• 2005

Traditional watermarking technologies are symmetric method which embedding and detection keys are same. Although the symmetric watermarking method is easy to detect the watermark, this method has weakness against to malicious attacks to remove or modify the watermark information when the symmetric key is disclosure. Recently, the asymmetric watermarking method that has different keys to embed and detect is watched several researchers as a next generation watermarking technology. In this paper, we have expanded search space of secret key using the solution set of linear simultaneous equations. Secret key is generated by secure linear transformation method to prevent of guessing secret key from public key, and the correlation value between secret key and public key is high. At theresults, the multi bits information can be embedded and high correlation value was detected after JPEG compression.

• Journal of Multimedia Information System
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• v.2 no.4
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• pp.303-310
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• 2015

Vulnerable road users such as bike, motorcycle, small automobiles, and etc. are easily attacked or threatened with bigger vehicles than them. So this paper suggests a new approach two-wheelers detection system riding on people based on modified histogram of oriented gradients (HOGs) which is weighted by curvature and local correlation coefficient. This correlation coefficient between two variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using the curvature of Gaussian and Histogram of Oriented Gradients (HOG) which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the correlation coefficient between the area of each cell and one of bike, can be used as the weighting factor in process for normalizing the HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. The experimental results validate the effectiveness of our proposed algorithm show higher than that of the traditional method and under challenging, such as various two-wheeler postures, complex background, and even conclusion.

• Smart Media Journal
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• v.1 no.3
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• pp.48-55
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• 2012

In general, background subtraction based methods are used to detect the moving objects in visual tracking applications. In this paper we employed background subtraction based scheme to detect the temporarily stationary objects. We proposed two schemes for stationary object detection and we compare those in terms of detection performance and computational complexity. In the first approach we used single background and in the second approach we used dual backgrounds, generated with different learning rates, in order to detect temporarily stopped object. Finally, we used normalized cross correlation (NCC) based image comparison to monitor and track the detected stationary object in a video scene. The proposed method is robust with partial occlusion, short time fully occlusion and illumination changes, as well as it can operate in real time.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.2
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• pp.23-34
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• 1995

This paper is concerned with effective and reliable tool breakage detection method using pattern characteristics of feed motor current in milling operations. Correlation coefficient is derived from the feature vector of signal for two consecutive which are extracted feed motor current over three spindle revolutions. The changing pattern of correlation coefficient is continuously compared to detect tool breakage and monitor cutting conditions. This proposed monitoring scheme is not affected by different tools, friction of motion, and varying cutting conditions and material shapes. Experimental results are presented to support the proposed monitoring scheme.

• Proceedings of the KSRS Conference
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• v.1
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• pp.236-238
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• 2006

An algorithm for detection of yellow sand aerosols has been developed with infrared bands from Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-functional Transport Satellite-1 Replacement (MTSAT-1R) data. The algorithm is the hybrid algorithm that has used two methods combined together. The first method used the differential absorption in brightness temperature difference between $11{\mu}m$ and $12{\mu}m$ (BTD1). The radiation at 11 ${\mu}m$ is absorbed more than at 12 ${\mu}m$ when yellow sand is loaded in the atmosphere, whereas it will be the other way around when cloud is present. The second method uses the brightness temperature difference between $3.7{\mu}m$ and $11{\mu}m$ (BTD2). The technique would be most sensitive to dust loading during the day when the BTD2 is enhanced by reflection of $3.7{\mu}m$ solar radiation. We have applied the three methods to MTSAT-1R for derivation of the yellow sand dust and in conjunction with the Principle Component Analysis (PCA), a form of eigenvector statistical analysis. As produced Principle Component Image (PCI) through the PCA is the correlation between BTD1 and BTD2, errors of about 10% that have a low correlation are eliminated for aerosol detection. For the region of aerosol detection, aerosol index (AI) is produced to the scale of BTD1 and BTD2 values over land and ocean respectively. AI shows better results for yellow sand detection in comparison with the results from individual method. The comparison between AI and OMI aerosol index (AI) shows remarkable good correlations during daytime and relatively good correlations over the land.