• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.509-522
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• 2018

Purpose: The purpose of this study was to propose more accurate mathematical model which can represent result of government quality assurance activity, especially corrective action and flaw. Methods: The collected data during government quality assurance activity was represented through histogram. To find out which distributions (Poisson distribution, Zero-Inflated Poisson distribution) could represent the histogram better, this study applied Pearson's correlation coefficient. Results: The result of this study is as follows; Histogram of corrective action during past 3 years and Zero-Inflated Poisson distribution had strong relationship that their correlation coefficients was over 0.94. Flaw data could not re-parameterize to Zero-Inflated Poisson distribution because its frequency of flaw occurrence was too small. However, histogram of flaw data during past 3 years and Poisson distribution showed strong relationship that their correlation coefficients was 0.99. Conclusion: Zero-Inflated Poisson distribution represented better than Poisson distribution to demonstrate corrective action histogram. However, in the case of flaw data histogram, Poisson distribution was more accurate than Zero-Inflated Poisson distribution.

• MALSORI
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• v.55
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• pp.131-142
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• 2005

A mismatch between the training and the test conditions often causes a drastic decrease in the performance of the speech recognition systems. In this paper, non-linear transformation techniques based on histogram equalization in the acoustic feature space are studied for reducing the mismatched condition. The purpose of histogram equalization(HEQ) is to convert the probability distribution of test speech into the probability distribution of training speech. While conventional histogram equalization methods consider only the probability distribution of a test speech, for noise-corrupted test speech, its probability distribution is also distorted. The transformation function obtained by this distorted probability distribution maybe bring about miss-transformation of feature vectors, and this causes the performance of histogram equalization to decrease. Therefore, this paper proposes a new method of calculating noise-removed probability distribution by using assumption that the CDF of noisy speech feature vectors consists of component of speech feature vectors and component of noise feature vectors, and this compensated probability distribution is used in HEQ process. In the AURORA-2 framework, the proposed method reduced the error rate by over $44\%$ in clean training condition compared to the baseline system. For multi training condition, the proposed methods are also better than the baseline system.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.705-712
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• 2009

Histogram is the oldest and most widely used density estimator for presentation and exploration of observed univariate data. The structure of a histogram really depends on the number of bins and the width of the bins, so that slight changes on bins can produce totally different shape of a histogram. In order to solve this problem the fuzzy histogram was introduced and the result was good enough (Loquin and Strauss, 2008). In particular, when estimating loss distribution related with operational risk a histogram has been widely used. In this article, instead of an ordinary histogram we try to use a fuzzy histogram for estimating loss distribution and show that a fuzzy histogram provide more stable results.

• ETRI Journal
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• v.24 no.1
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• pp.23-30
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• 2002

MPEG-7 Visual Standard specifies a set of descriptors that can be used to measure similarity in images or video. Among them, the Edge Histogram Descriptor describes edge distribution with a histogram based on local edge distribution in an image. Since the Edge Histogram Descriptor recommended for the MPEG-7 standard represents only local edge distribution in the image, the matching performance for image retrieval may not be satisfactory. This paper proposes the use of global and semi-local edge histograms generated directly from the local histogram bins to increase the matching performance. Then, the global, semi-global, and local histograms of images are combined to measure the image similarity and are compared with the MPEG-7 descriptor of the local-only histogram. Since we exploit the absolute location of the edge in the image as well as its global composition, the proposed matching method can retrieve semantically similar images. Experiments on MPEG-7 test images show that the proposed method yields better retrieval performance by an amount of 0.04 in ANMRR, which shows a significant difference in visual inspection.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.1
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• pp.14-21
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• 2008

In this paper, we propose an adaptive contrast enhancement method using dynamic range segmentation. Histogram Equalization (HE) method is widely used for contrast enhancement. However, histogram equalization method is not suitable for commercial display because it may cause undesirable artifacts due to the significant change in brightness. The proposed algorithm segments the dynamic range of the histogram and redistributes the pixel intensities by the segment area ratio. The proposed method may cause over compressed effect when intensity distribution of an original image is concentrated in specific narrow region. In order to overcome this problem, we introduce an adaptive scale factor. The experimental results show that the proposed algorithm suppresses the significant change in brightness and provides wide histogram distribution compared with histogram equalization.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1519-1527
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• 2015

TFT-LCD automatic defect inspection system for detecting defects in place of the visual tester does pre-processing, candidate defect pixel detection, and recognition and classification through a blob analysis. An over-detection result of defects acts as an undue burden of blob analysis for recognition and classification. In this paper, we propose defect detection method based on the histogram distribution modeling of TFT-LCD image to minimize over-detection of candidate defective pixels. Primary defect candidate pixels are detected estimating the skewness of the luminance distribution histogram of the background pixels. Based on the detected defect pixels, the defective pixels other than noise pixels are detected using the distribution histogram model of the local area. Experimental results confirm that the proposed method shows an excellent defect detection result on the image containing the various types of defects and the reduction of the degree of over-detection as well.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.61-73
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• 2012

This paper proposes a histogram specification based image enhancement method, which uses the brightness mean and variance of an image to maximize the entropy of the image. In our histogram specification step, the Gaussian distribution is used to fit the input histogram as well as produce the target histogram. Specifically, the input histogram is fitted with the Gaussian distribution whose mean and variance are equal to the brightness mean(${\mu}$) and variance(${\sigma}2$) of the input image, respectively; and the target Gaussian distribution also has the mean of the value ${\mu}$, but takes as the variance the value which is determined such that the output image has the maximum entropy. Experimental results show that compared to the existing methods, the proposed method preserves the mean brightness well and generates more natural looking images.

• Phonetics and Speech Sciences
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• v.2 no.3
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• pp.127-134
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• 2010

Additive noise and channel mismatch strongly degrade the performance of speaker verification systems, as they distort the features of speech. In this paper a histogram transformation technique is presented to improve the robustness of text-independent speaker verification systems. The technique transforms the features extracted from speech such that their histogram is conformed to a reference distribution. The effect of different standard deviations for the reference distribution is investigated. Experimental results indicate that, in channel mismatched environments, the proposed technique offers significant improvements over existing techniques. We also verify performance improvement of the proposed method using statistics.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.39-47
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• 2016

In this paper, we propose an approach for real time computation of rayleigh CLAHE using a FPGA. The contrast enhancement technique should be applied in thermal equipment having a low contrast image. And thermal equipment must be processed in real time. The CLAHE is an improved algorithm based Histogram Equalization, but the HW design is complex. A value greater than a given threshold in CLAHE should be equally distributed on the other histogram bin, this process requires iterations for the distribution. But implementation of this processing in the FPGA is constrained, so this section was implemented on the assumption of the histogram distribution or modified the operation process or implemented separately in the CPU. In this paper, we designed a distinct redistribution operation in two stages. So FPGA was designed for easy, this was designed to be distributed evenly without the assumptions and constraints. In addition, we have designed a CLAHE with the rayleigh distribution to the FPGA. The simulation shows that the proposed method provides a better image quality in the thermal image.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.1020-1024
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• 1987

Image segmentation based on the curvature of bi-directiona distribution functions of histogram with no mode informations is proposed. The curvature is an oscillating function and can be approximated to a polynomial form with a least square method using the Chebyshev basis. Nonhomogeneous linea equations are solved by Gauss-elimination method. In the proposed algorithm, critical points of the curvature are obtained on each direction to compensate the segmentation parameters, which can be ignored in only one-directional histogram.