• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.511-513
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• 2002

본 논문에서는 영상에 Salt-Pepper와 같은 임펄스 잡음이 존재하는 영상에 대한 잡음 제거는 기존의 잡음제거 방법인 미디언 필터를 이용하여 잡음을 제거할 수 있지만 임펄스 잡음이 아닌 비임펄스 잡음이 포함된 영상에 대해서는 미디언 필터를 이용하여 비임펄스 잡음이 제거되지 않으므로 임펄스 잡음이 아닌 비임펄스 잡음이 존재하는 영상에 대한 잡음 제거를 형태학적 연산을 이용하여 잡음 제거하는 방법을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.11
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• pp.1078-1083
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• 2013

At the ubiquitous age, applications of Wireless Personal Area Network (WPAN) technology using LEDs are in progress. However, visible light communication using LED have weakness, which deteriorates performance of communication. To reduce information losses, which is caused by optical noise, such as incandescent lamps, fluorescent lamps, sunbeam etc., proposed channel coding scheme, double binary turbo codes. In this paper, encoding scheme of the proposed system is described and simulation results are analyzed. We had expected improved performance by using double binary turbo codes. Finally, performances of the proposed system came up to our expectations.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.316-320
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• 2016

In this paper, we presents a pattern recognition by considering the spatial co-occurrence among micro-patterns of texture images. The micro-patterns of texture image have been extracted by local binary pattern based on median(MLBP) of block image, and the recognition process is based on co-occurrence among MLBPs. The MLBP is applied not only to consider the local character but also analyze the pattern in order to be robust noise, and spatial co-occurrence is also applied to improve the recognition performance by considering the global space of image. The proposed method has been applied to recognized 17 RGB images of 120*120 pixels from Mayang texture image based on Euclidean distance. The experimental results show that the proposed method has a texture recognition performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.221-230
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• 2002

This paper presents a new moving object segmentation algorithm using markov random field. The algorithm is based on signal detection theory. That is to say, motion of moving object is decided by binary decision rule, and false decision is corrected by markov random field model. The procedure toward complete segmentation consists of two steps: motion detection and object segmentation. First, motion detection decides the presence of motion on velocity vector by binary decision rule. And velocity vector is generated by optical flow. Second, object segmentation cancels noise by Bayes rule. Experimental results demonstrate the efficiency of the presented method.

• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.912-919
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• 2005

When we apply binary classification to multi-class classification for text categorization, we use the One-Against-All method generally, However, this One-Against-All method has a problem. That is, documents of a negative set are not labeled by human. Thus, they can include many noisy documents in the training data. In this paper, we propose that the Sliding Window technique and the EM algorithm are applied to binary text classification for solving this problem. We here improve binary text classification through extracting noise documents from the training data by the Sliding Window technique and re-assigning categories of these documents using the EM algorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.3
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• pp.6-12
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• 1984

The basic binary quantized first-order digital phase locked loop (DPLL) is modified in order to reduce the aquisition time and steadyftate phase error. Adding the loop that corrects the phase difference by detecting the falling zero-crossing time, an effort for the improving the performance is performed and the performance compared with that of the basic DPLL. Using a graphical method, the phase locking processes of the modified DPLL for a phase step and a frequency step input are depicted visually in the absence of noise. The performance of the modified DPLL for a sinusoidal input added narrow band random noise is evaluated using the Chapman-Kolmogorov equation. This approach is verified by direct computer simulation. The steady-state phase error and the average aquisition time of the modified DPLL are compared with those of the basic DPLL, It is shown that the aquisition time of the modified DPLL is shortened about twice, also, as signal to noise ratio increases, the effect of the modification increases and the steady-state phase error approaches to zero.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.54.4-54
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• 2002

1.Introduction 2. Channel Equalizer Using Adaptive Neural Network 3. Data Modulation and Demodulation Using Haar Transform 4. Binary Signal Transmission Using Haar Transform 5. Conclusion

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.83-86
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• 2004

The variation of the directional properties of an image is used to extract the iris code for human identification. In order to conserve the original information while minimizing the effect of noise, scale-space filtering is applied. Resulting binary codes have been tested on a set of 272 iris images obtained from 18 persons.

• Journal of IKEEE
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• v.23 no.4
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• pp.1465-1468
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• 2019

The image noise improvement algorithm proposed in this paper extracts the boundary line by using the window of the binarized image to detect the gesture motion. Boundary line blurring is prevented by improving Gaussian noise generated during video output. To improve gesture recognition in low-light environments, an image noise enhancement algorithm has been designed to provide an output image close to the base image. Analyzing the experimental results, we found almost 10% improvement in the results compared to the results of the existing Median filter.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.50-53
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• 2000

It is effectively removed noise in the image using FCNN(Fuzzy Cellular Neural Network) applying fuzzy theory to CNN(Cellular Neural Network) structure and HD(Hausdorff Distance) commonly used measures for object matching. HD calculates the distance between two point set of pixels in two-dimensional binary images without establishing correspondence. Also, this method is proposed in order to improve the operation speed. In this paper, $\alpha$-LTSHD(Least Trimmed Square HD) operator applying $\alpha$-Trimmed to LTSHD, one field of HD, is applied to FCNN structure, and it is proposed as the modified method in order to remove noise in the image. Also, it is made a comparison with the other filters by using MSE and SNR after removing noise using the FCNNS which are applied $\alpha$-LTSHD operator through the computer simulation. In a result, FCNN performance which is applied the proposed $\alpha$-LTSHD demonstrated the superiority to the other filters in the noise removal.