• Proceedings of the KSME Conference
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• 2001.06d
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• pp.408-413
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• 2001

Numerical analysis on the three-dimensional laminar flows (Re=1000) and heat transfer in a rectangular channel with punched longitudinal vortex generator have been conducted to explore the heat transfer enhancement and the combined effect of the angle of attack ${\alpha}$ and the lovour angle ${\beta}$. Rectangular winglets have been used as vortex generators. Velocity and temperature fields and spanwise averaged Nu and friction factor were presented. Enhancement of heat transfer and flow loss penalty are evidenced. The results show performance characteristics allowing a reduction in heat transfer surface area of 62% for fixed heat duty and for fixed pumping power compared with that of channel flow without vortex generator. However, adding lovour angle to the vortex generator shows no positive effect on the heat transfer enhancement.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.1
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• pp.60-67
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• 2015

This paper proposes an image-dependent color image enhancement method that uses adaptive luminance enhancement and color emphasis. It effectively enhances details of low-light regions while maintaining well-balanced luminance and color information. To compare the structure similarity and naturalness, we used the tone mapped image quality index (TMQI). The proposed method maintained better structure similarity in the enhanced image than did the space-variant luminance map (SVLM) method or the adaptive and integrated neighborhood dependent approach for nonlinear enhancement (AINDANE). The proposed method required the smallest computation time among the three algorithms. The proposed method can be easily implemented using the field-programmable gate array (FPGA), with low hardware resources and with better performance in terms of similarity.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3E
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• pp.110-112
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• 2003

There have been numerous studies on the enhancement of the noisy speech signal. In this paper, we propose a completely new speech enhancement scheme, that is, a filtering of a dissonant frequency (especially F# in each octave of the tempered scale) based on the fundamental frequency which is developed in frequency domain. In order to evaluate the performance of the proposed enhancement scheme, subjective tests (MOS tests) were conducted. The subjective test results indicate that the proposed method provides a significant gain in audible improvement especially for speech contaminated by colored noise and speaking in a husky voice. Therefore when the filter is employed as a pre-filter for speech enhancement, the output speech quality and intelligibility is greatly enhanced.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1603-1613
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• 1995

The goal of enhancement is to improve the perceptual aspect and visual appearance of images for human viewers. The objectives of image enhancement vary according to its specific application and an image enhancement algorithms used for a specific objective may not be accepted in some other applications. In this paper we review some of conventional enhancement techniques, such as global histogram equalization(GHE), local histogram equalization(LHE), clipped histogram equalization(CHE). We also describe some modified version of these algorithms. The proposed method is to detect detail information. We distinquish edge from nonedge and apply histigram equalization respectively. Simulation results demonstrate the performance of the proposed method for medical image.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.52-58
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• 2014

Exact histogram specification (EHS) transforms the histogram of an input image into the specified histogram. In the conventional EHS techniques, the pixels are first sorted according to their graylevels, and the pixels that have the same graylevel are further differentiated according to the local average of the pixel values and the edge strength. The strictly ordered pixels are then mapped to the desired histogram. However, since the conventional sorting method is inherently dependent on the initial graylevel-based sorting, the contrast enhancement capability of the conventional EHS algorithms is restricted. We propose a modified EHS algorithm considering the just noticeable difference. In the proposed algorithm, the edge pixels are pre-processed such that the output edge pixels obtained by the modified EHS can result in the local contrast enhancement. Moreover, we introduce a new sorting method for the pixels that have the same graylevel. Experimental results show that the proposed algorithm provides better image enhancement performance compared to the conventional EHS algorithms.

• Journal of Broadcast Engineering
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• v.8 no.1
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• pp.11-18
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• 2003

In this paper, we introduce a novel signal quality enhancement algorithm with a perceptual interference analysis and perceptual convolutional noise suppression. A perceptual convolutional noise is reflected in the audible disturbance that can still be recognized after the additional noise suppression and tonality change which is caused by the noise energy excitation. The enhancement system is organized with a perceptual additional noise suppression part and a perceptual convolutional noise suppression part. Experimental results show that these two parts have an equivalent quality enhancement performance.

• MALSORI
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• no.57
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• pp.153-164
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• 2006

The MMSE-STSA based speech enhancement algorithm is widely used as a preprocessing for noise robust speech recognition. It weighs the gain of each spectral bin of the noisy speech using the estimate of noise and signal power spectrum. In this paper, we investigate the influence of parameters used to estimate the speech signal and noise power in MMSE-STSA upon the recognition performance of noisy speech. For experiments, we use the Aurora2 DB which contains noisy speech with subway, babble, car, and exhibition noises. The HTK-based continuous HMM system is constructed for recognition experiments. Experimental results are presented and discussed with our findings.

• Phonetics and Speech Sciences
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• v.1 no.3
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• pp.95-102
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• 2009

In this paper, an efficient target speech detection algorithm is proposed for the performance improvement of multi-input speech enhancement. Using the normalized cross correlation value between two selected channels, the proposed algorithm estimates the probabilistic distribution function of the value from the pure noise interval. Then, log-likelihoods are calculated with the function and the normalized cross correlation value to detect the target speech interval precisely. The detection results are applied to the generalized sidelobe canceller-based algorithm. Experimental results show that the proposed algorithm significantly improves the speech recognition performance and the signal-to-noise ratios.

• Journal of the Korean Institute of Navigation
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• v.24 no.4
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• pp.227-234
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• 2000

In general, neural networks are widely used for the category classification of multispectral images. Since the input multispectral images into neural networks we, however, low contrast images, neural networks converge very slowly and are of bad performance. To overcome this problem, we propose a new image enhancement method which consists of smoothing process, finding the main valley and enhancement process. In addition the enhanced images by the proposed method are used as the input of neural networks for the category classification. When the new category classification method is applied to multispectral LANDSAT TM images, we verified that the neural networks converge very lastly and that the overall category classification performance is improved.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.185-193
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• 2022

There have been various studies in Korea to develop a %IMF(Intramuscular Fat Percentage) estimation method suitable for Hanwoo. Recently, a %IMF estimation method using a convolutional neural network (CNN), a kind of deep learning method among artificial intelligence methods, has been studied. In this study, we performed a performance comparison when various preprocessing methods were applied to the %IMF estimation of ultrasound images using CNN as mentioned above. The preprocessing methods used in this study are normalization, histogram equalization, edge enhancement, and a method combining normalization and edge enhancement. When estimating the %IMF of Hanwoo by the conventional method that did not apply preprocessing in the experiment, the accuracy was 98.2%. The other hand, we found that the accuracy improved to 99.5% when using preprocessing with histogram equalization alone or combined regularization and edge enhancement.