• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.450-463
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• 2018

Sound based machine fault diagnosis is the process consisting of detecting automatically the damages that affect the machines by analyzing the sounds they produce during their operating time. The collected sounds being inevitably corrupted by random disturbance, the most important part of the diagnosis consists of discovering the hidden elements inside the data that can reveal the faulty patterns. This paper presents a novel feature extraction methodology that combines various digital signal processing and pattern recognition methods for the analysis of the sounds produced by the drills. Using the Fourier analysis, the magnitude spectrum of the sounds are extracted, converted into two-dimensional vectors and uniformly normalized in such a way that they can be represented as 8-bit grayscale images. Histogram equalization is then performed over the obtained images in order to adjust their very poor contrast. The obtained contrast enhanced images will be used as the features of our diagnosis system. Finally, principal component analysis is performed over the image features for reducing their dimensions and a nonlinear classifier is adopted to produce the final response. Unlike the conventional features, the results demonstrate that the proposed feature extraction method manages to capture the hidden health patterns of the sound.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.3
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• pp.330-338
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• 2011

Odometry is the critical factor to estimate the location of the robot. In the mobile robot with wheels, odometry can be performed using the information from the encoder. However, the information of location in the encoder is inaccurate because of the errors caused by the wheel's alignment or slip. In general, visual odometer has been used to compensate for the kinetic errors of robot. In case of using the visual odometry under some robot system, the kinetic analysis is required for compensation of errors, which means that the conventional visual odometry cannot be easily applied to the implementation of the other type of the robot system. In this paper, the novel visual odometry, which employs only the single camera toward the ground, is proposed. The camera is mounted at the center of the bottom of the mobile robot. Feature points of the ground image are extracted by using median filter and color contrast filter. In addition, the linear and angular vectors of the mobile robot are calculated with feature points matching, and the visual odometry is performed by using these linear and angular vectors. The proposed odometry is verified through the experimental results of driving tests using the encoder and the new visual odometry.

• Phonetics and Speech Sciences
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• v.1 no.3
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• pp.19-28
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• 2009

This paper reports experimental findings about the duration feature of the acoustic components of English stops in Korean speakers' voicing perception. In our experiment, 35 participants discriminated between recorded stimuli and digitally transformed stimuli with different duration features from the original stimuli. 72 sets of paired stimuli are generated to test the effects of the duration feature in various phonetic contexts. The result of our experiment is a complicated cross-tabulation with 540 cells defined by five categorical independent variables plus one response variable. To find a meaningful generalization out of this complex frequency table, we ran logit log-linear regression analyses. Surprisingly, we have found that there is no single effect of the duration feature in all phonetic contexts on Korean speakers' perception of the voicing contrasts of English stops. Instead, the logit log-linear analyses reveal that there are interaction effects among phonetic contexts (=C), the places of articulation of stops (=P), and the voicing contrast (=V), and among duration (=T), phonetic contexts, and the places of articulation. To put it in mathematical terms, the distribution of the data can be explained by a simple log-linear equation, logF=${\mu}+{\lambda}CPV+{\lambda}TCP$.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.115-120
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• 2005

In this paper, we propose a new robust content-based musical genre classification algorithm using multi-feature clustering(MFC) method. In contrast to previous works, this paper focuses on two practical issues of the system dependency problem on different input query patterns(or portions) and input query lengths which causes serious uncertainty of the system performance. In order to solve these problems, a new approach called multi-feature clustering(MFC) based on k-means clustering is proposed. To verify the performance of the proposed method, several excerpts with variable duration were extracted from every other position in a queried music file. Effectiveness of the system with MFC and without MFC is compared in terms of the classification accuracy. It is demonstrated that the use of MFC significantly improves the system stability of musical genre classification performance with higher accuracy rate.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1121-1135
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• 2005

This paper proposes a moving object extraction method using the contrast map and salient points. In order to make the contrast map, we generate three-feature maps such as luminance map, color map and directional map and extract salient points from an image. By using these features, we can decide the Attention Window(AW) location easily The purpose of the AW is to remove the useless regions in the image such as background as well as to reduce the amount of image processing. To create the exact location and flexible size of the AW, we use motion feature instead of pre-assumptions or heuristic parameters. After determining of the AW, we find the difference of edge to inner area from the AW. Then, we can extract horizontal candidate region and vortical candidate region. After finding both horizontal and vertical candidates, intersection regions through logical AND operation are further processed by morphological operations. The proposed algorithm has been applied to many video sequences which have static background like surveillance type of video sequences. The moving object was quite well segmented with accurate boundaries.

• Phonetics and Speech Sciences
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• v.2 no.3
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• pp.91-99
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• 2010

This paper reports on an identification test where KFL learners identified the Korean three-way laryngeal contrast in the phrase-initial position, when the phrase-initial tone was systematically manipulated. It turns out that heritage learners have some sensitivity to phrase-initial tone and show a plain-aspirated alternation in their identification according to the phrase-initial tone, as native speakers do, whereas non-heritage students do not show such tone sensitivity. However, after a weekly prosody training, second-year non-heritage students have shown a significant improvement in their performance. This paper clearly shows that the phrase-initial tone plays a critical role in distinguishing laryngeal features of Korean obstruents, and also suggests that prosody including the tone-segment correlation should be incorporated in the KFL curriculum.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.14-19
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• 2017

In this paper, a fused illumination mechanism for detecting surface defects in steel plates was designed by applying the discriminant function that can differentiate the contrast of defects and non-defects. There is low contrast, non-uniformity, and no feature characteristics in steel plate surfaces. The fused illumination mechanism is devised, based on those characteristics. Optimum parameters of the fused illumination mechanism are determined by applying the discriminant function after acquiring the defect image in steel plate surfaces. The performance of the proposed mechanism is verified by experminets.

• Korean Journal of Veterinary Research
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• v.59 no.2
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• pp.105-108
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• 2019

A 4-year-old cat was referred for a suspected pulmonary mass. True diaphragmatic hernia presence was diagnosed via computed tomography (CT). There was a thin membrane covering the diaphragmatic defect. The membrane was thinner than the diaphragm. After contrast injection, the membrane was less enhanced than that of the normal diaphragm. The membrane was identified as a remnant of the parietal pleura. In addition, contrast-enhanced CT images provided clarity in viewing the herniated liver and falciform fat. A thinner membrane, covering the diaphragmatic defect, and attached to the thicker normal diaphragm, is considered a unique CT feature of true diaphragmatic hernia.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.166-179
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• 2021

Recently, with the development of technology, computer vision research based on the human visual system has been actively conducted. Saliency maps have been used to highlight areas that are visually interesting within the image, but they can suffer from low performance due to external factors, such as an indistinct background or light source. In this study, existing color, brightness, and contrast feature maps are subjected to multiple shape and orientation filters and then connected to a fully connected layer to determine pixel intensities within the image based on location-based weights. The proposed method demonstrates better performance in separating the background from the area of interest in terms of color and brightness in the presence of external elements and noise. Location-based weight normalization is also effective in removing pixels with high intensity that are outside of the image or in non-interest regions. Our proposed method also demonstrates that multi-filter normalization can be processed faster using parallel processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.539-557
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• 2013

A novel multifocus image fusion algorithm based on NSCT is proposed in this paper. In order to not only attain the image focusing properties and more visual information in the fused image, but also sensitive to the human visual perception, a local multidirection variance (LEOV) fusion rule is proposed for lowpass subband coefficient. In order to introduce more visual saliency, a modified local contrast is defined. In addition, according to the feature of distribution of highpass subband coefficients, a direction vector is proposed to constrain the modified local contrast and construct the new fusion rule for highpass subband coefficients selection The NSCT is a flexible multiscale, multidirection, and shift-invariant tool for image decomposition, which can be implemented via the atrous algorithm. The proposed fusion algorithm based on NSCT not only can prevent artifacts and erroneous from introducing into the fused image, but also can eliminate 'block effect' and 'frequency aliasing' phenomenon. Experimental results show that the proposed method achieved better fusion results than wavelet-based and CT-based fusion method in contrast and clarity.