• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.727-734
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• 2014

Digital processing technologies are being studied in various areas of image compression, recognition and recovery. However, image deterioration still occurs due to the noises in the process of image acquisition, storage and transmission. Generally in the typical noises which are included in the images, there are Gaussian noise and the mixed noise where the Gaussian noise and impulse noise are overlapped and in order to remove these noises, various researches are being executed. In order to preserve the edge and effectively remove mixed noises, image recovery filter algorithm was suggested in this study which sets and processes the adaptive weight using the median values and average values after noise judgment. Additionally, existing methods were compared through simulations and PSNR(peak signal to noise ratio) was used as a judgment standard.

• Phonetics and Speech Sciences
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• v.7 no.1
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• pp.21-26
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• 2015

The aim of this study is to synthesize pathological breathy voice and to make a cepstral peak prominence (CPP) table following breathiness ranks by cepstral analysis to supplement reliability of the perceptual auditory judgment task. KlattGrid synthesizer included in Praat was used. Synthesis parameters consist of two groups, i.e., constants and variables. Constant parameters are pitch, amplitude, flutter, open phase, oral formant and bandwidth. Variable parameters are breathiness (BR), aspiration amplitude (AH), and spectral tilt (TL). Five hundred sixty samples of synthetic breathy vowel /a/ for male were created. Three raters participated in ranking of the breathiness. 217 were proved to be inadequate samples from perceptual judgment and cepstral analysis. Finally, 343 samples were selected. These CPP values and other related parameters from cepstral analysis are classified under four breathiness ranks (B0~B3). The mean and standard deviation of CPP is $16.10{\pm}1.15$ dB(B0), $13.68{\pm}1.34$ dB(B1), $10.97{\pm}1.41$ dB(B2), and $3.03{\pm}4.07$ dB(B3). The value of CPP decreases toward the severe group of breathiness because there is a lot of noise and a small quantity of harmonics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1725-1731
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• 2013

Recently, as industrial society is developed as high digital information age, image processing is used in a variety of areas. However, image deterioration is still occurred by several noises in the data processing, and different kinds of researches are in progress for noise removal. Therefore, this paper limited the modified median filter by using standard deviation to removes impulse noise. The proposed algorithms divided into noise detection and noise removal, the noise free pixel is maintained, the noise pixel filtered. And it was compared with the existing methods for its objective judgment, using PSNR(peak signal to noise ratio) as standard criteria.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.104-115
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• 2005

Median filters in the signal processing have been most widely used and have demonstrated the strongest effects. This paper proposes the adaptive median filters with noise detection. The proposed basic algorithm of the filters is to judge whether or not the noises exist on the ground of The Noise Judgment Standards. Just in case the existence of the noises is verified by the algorithm, it takes the median filter. In order to judge the existence of the noises by the algorithm, this paper introduced the noise detection method by local central variance. As a result of comparing and analyzing the features and performance of the proposed filters and the existing [5]-[10] filters on the same conditions, it was verified that the former proved to be better than the latter, Observed even by naked eyes, it was similar, too. Accordingly, it's proved that the adaptive median filters by local central variance are useful in removing the impulse noise of the median filter and reinforce the edge preservation ability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.922-924
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• 2015

Recently, the image processing technologies using the public media such as the film, TV, camera and advertisement have been rapidly developed. However, the deterioration occurs with the image in the process of data processing, transmission and storage, and the typical cause of such deterioration is the salt and pepper noise. Typical filters to remove the salt and pepper noise include CWMF(center weighted median filter) and AMF(adaptive median filter) but such filters bring more or less insufficient characteristics of noise removal and visual error as the noise density gets higher. Thus, this paper proposed the median filter which applied the local mask segmented to 4 areas in order to remove the salt and pepper noise effectively and used PSNR(peak signal to noise ratio) as a criterion of judgment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.214-216
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• 2019

Recently, as the use of digital equipment increases in various fields, the importance of image and signal processing is increasing. However, many kinds of noise occur in the digital signal during transmission and reception, and this noise greatly affects the final output of the system. In this paper, we propose an algorithm that effectively restores the image by removing noise according to pixel similarity in a mixed noise environment with impulse noise and AWGN. The proposed algorithm sets the reference value according to the noise type and applies the filtering to pixels similar to the reference value to obtain the final output. Simulation results show that the proposed algorithm has good noise canceling performance and compared with conventional methods using PSNR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.404-406
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• 2021

In modern society, artificial intelligence and automation are being applied in various fields due to the development of the 4th industrial revolution and IoT technology. In particular, systems with a high proportion of image processing, such as automated processes, intelligent CCTV, medical industry, robots, and drones, are susceptible to external factors noise. In this paper, we propose a digital filter based on noise estimation and weights to reconstruct an image in a complex noise environment. The proposed algorithm classifies the types of noise using noise judgment, and determines the noise level of the filtering mask to switch the filtering process to obtain the final output. In order to verify the performance of the proposed algorithm, simulation was conducted, compared with the existing filter algorithm, and the results were analyzed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.586-594
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• 2018

In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.932-935
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• 2015

Recently, the image system is utilized in several fields due to the development of multimedia technology. However, the noise occurs according to various causes in the process of image data processing. The noises added to the image include several types according to the cause and shape, and the salt and pepper noise is one of the typical noise types. Thus, this paper proposed the median filter algorithm using the estimated mask in order to remove the salt and pepper noise effectively and also compared this algorithm with the current methods using PSNR(peak signal to noise ratio) as a criterion of judgment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.281-284
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• 2015

Digital image processing is utilized in various application fields by rapid development of memory cell. However, the noise occurs with various causes in the process of data processing process and various methods have been studied in order to remove such noises. In general, the image is damaged by the mixed noise which has different characteristics each other. This paper proposed a filter algorithm which processes the data according to shape of noise in order to mitigate the impact of the mixed noise added to the image. In addition, this paper compared this filter algorithm with the current methods and used PSNR(peak signal to noise ratio) as a criterion of judgment.