• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.587-594
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• 2005

In this paper, a robust correlation-based video tracking is proposed to track a moving object in correlated image sequences. A correlation-based video tracking algorithm seeks to align the incoming target image with the reference target block image, but has critical problems, so called a false-peak problem and a drift phenomenon (correlator walk-off. The false-peak problem is generally caused by highly correlated background pixels with similar intensity of a moving target and the drift phenomenon occurs when tracking errors accumulate from frame to frame because of the nature of the correlation process. At first, the false-peaks problem for the ordinary correlation-based video tracking is investigated using a simple mathematical analysis. And, we will suggest a robust selective-attention correlation measure with a gradient preprocessor combined by a drift removal compensator to overcome the walk-off problem. The drift compensator adaptively controls the template block size according to the target size of interest. The robustness of the proposed method for practical application is demonstrated by simulating two real-image sequences.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.51.1-51.1
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• 2016

Turbulent motions produce density and magnetic field fluctuations. Correlation between density and magnetic field fluctuations are important for interpretation of observations, such as the rotation measure (RM) and dispersion measure (DM). We study the several factors that can affect the correlation between two. In particular, we numerically investigate how the correlation time of driving affects the correlation between density and magnetic field. We perform compressible MHD turbulence simulations at different sonic Mach number and consider two different driving schemes - continuously changing driving and delta-correlated driving. The continuously changing driving results in strong anti-correlation between density and magnetic field when sonic and Alfvenic Mach numbers are similar unity. The delta-correlated driving produces virtually no correlation between two fields.

• PNF and Movement
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• v.12 no.1
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• pp.13-17
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• 2014

Purpose: To determine the normative data for the correlation of spinal, pelvic parameters with foot pressure in the young subjects. Methods: The subjects of this study were 39 patients in healthy adults. The Formetric-III was used to measure of spinal alignment. The pedoscan was used to measure of foot pressure. The correlation of trunk imbalance, trunk inclination, lateral deviation with foot pressure. The foot pressure measurement was consisted of maximal/mean pressure, weight contribution. Result: There was a negative correlation of trunk inclination with Max_R. There was a negative correlation of trunk inclination with Max_R. There was a positive correlation of trunk imbalance with Max_L. There was a positive correlation of lumbar lordosis with Mean_R_front, Lt. posterior weight distribution. There was a negative correlation of lumbar lordosis with Lt., Rt. in distribution There was a negative correlation of pelvic tilt with Mean_R_front, Lt. posterior weight distribution. There was a positive correlation of pelvic tilting with Rt. weight distribution, Lt. posterior weight distribution. There was a negative correlation of pelvic torsion with Lt. weight distribution, Rt. posterior weight distribution. There was a negative correlation of pelvic rotation with Lt. weight distribution, Lt. posterior weight distribution. Conclusion: The data obtained from the study may be used for future studies related to correlation of the spinal, pelvic deviation with foot pressure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.464-470
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• 2016

This paper presents a speech recognition database verification system using speech measures, and describes a speech measure extraction algorithm which is applied to this system. In our previous study, to produce an effective speech quality measure for the system, we propose a combination of various speech measures which are highly correlated with WER (Word Error Rate). The new combination of various types of speech quality measures in this study is more effective to predict the speech recognition performance compared to each speech measure alone. In this paper, we increase the system independency by employing GMM acoustic score instead of HMM score which is obtained by a secondary speech recognition system. The combination with GMM score shows a slightly lower correlation with WER compared to the combination with HMM score, however it presents a higher relative improvement in correlation with WER, which is calculated compared to the correlation of each speech measure alone.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.195-200
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• 2008

The accuracy of classifying pixels in HIRIS images is usually degraded by noisy bands since noisy bands may deform the typical shape of spectral reflectance. Proposed in this paper is a statistical method for noisy band removal which mainly makes use of the correlation coefficients between bands. Considering each band as a random variable, the correlation coefficient measures the strength and direction of a linear relationship between two random variables. While the correlation between two signal bands is high, existence of a noisy band will produce a low correlation due to ill-correlativeness and undirectedness. The application of the correlation coefficient as a measure for detecting noisy bands is under a two-pass screening scheme. This method is independent of the prior knowledge of the sensor or the cause resulted in the noise. The classification in this experiment uses the unsupervised k-nearest neighbor algorithm in accordance with the well-accepted Euclidean distance measure and the spectral angle mapper measure. This paper also proposes a hierarchical combination of these measures for spectral matching. Finally, a separability assessment based on the between-class and within-class scatter matrices is followed to evaluate the performance.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.263-270
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• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.2
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• pp.128-137
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• 2018

In this paper, we propose a novel class separability measure for radar signals. To reduce the sensitivity of the relative aspect angle between a target and radar, to evaluate the discriminatory power of radar signals, the proposed method first calculates the correlation coefficients between two radar cross sections (RCSs) or linearly shifts one-dimensional (1D) radar signals (i.e., high-resolution range profiles (HRRPs)), or rotates two 2D radar signals (i.e., inverse synthetic aperture radar (ISAR) images). Then, it uses the maximum correlation coefficient when two radar signals are best aligned. Next, the proposed method obtains new correlation-based discriminant matrices (CDM) using maximum correlation coefficients. Finally, the cumulative distribution function (CDF) in the CDM and the value corresponding to the specific probability in the CDF are obtained, and this value represents the discriminatory power of the radar signal. Experimental results show that the proposed method can accurately measure the target separability.

• Journal of Korean Society for Quality Management
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• v.22 no.1
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• pp.122-132
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• 1994

So far, the Taguchi Method has dealt with multiple quality characteristics under the assumption that they are independent. Since the relationships between quality characteristics are practically important, this study proposes a new performance measure considering the correlation among characteristics. In this paper, we impose weight on each characteristic and correlation among characteristics. The loss function of multiple characteristics is defined in accordance with combination of simple characteristic types, and it is divided into terms of loss that characteristic itself and the correlation among characteristics cause. And the proposed method uses the expected loss of multiple characteristics as the new performance measure. The data in literature are used to compare with the existing performance measures.

• Phonetics and Speech Sciences
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• v.2 no.1
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• pp.71-75
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• 2010

The PESQ is an objective speech quality evaluation measure that is known to have a high correlation with a subjective speech quality measure such as MOS. To examine whether it could be useful as an objective quality measure of synthetic speech, we carried out both subjective evaluation tests with MOS and DMOS and an objective evaluation test with PESQ for HMM-based Korean synthetic speech signals and analyzed the correlation between them. Experimental results have shown that the PESQ has correlations of 0.87 with MOS and 0.92 with DMOS. It means that the PESQ holds much promise for evaluating the quality of synthetic Korean speech.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.343-347
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• 2010

This paper presents an efficient image recognition method using the hybrid coefficient measure of correlation and distance. The correlation coefficient is applied to measure the statistical similarity by using Pearson coefficient, and distance coefficient is also applied to measure the spacial similarity by using city-block. The total similarity among images is calculated by extending the similarity between the feature vectors, then the feature vectors can be extracted by PCA and ICA, respectively. The proposed method has been applied to the problem for recognizing the 960(30 persons * 4 expressions * 2 lights * 4 poses) facial images of 40*50 pixels. The experimental results show that the proposed method of ICA has a superior recognition performances than the method using PCA, and is affected less by the environmental influences so as lighting.