• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.295-299
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• 2002

This paper presents an image contrast enhancement technique for improving low contrast images. We applied fuzzy logic to develop an image contrast enhancement technique in the viewpoint of considering that the low pictorial information of a low contrast image is due to the vaguness or fuzziness of the multivalued levels of brightness rather than randomness. The fuzzy image contrast enhancement technique consists of three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. In the stage of image fuzzification, we need to select a crossover point. To select the crossover point automatically the K-means algorithm is used. The problem of crossover point selection can be considered as the two-category, object and background, classification problem. The proposed method is applied to an experimental image with 256 gray levels and the result of the proposed method is compared with that of the histogram equalization technique. We used the index of fuzziness as a measure of image quality. The result shows that the proposed method is better than the histogram equalization technique.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.279-282
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• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) Model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved MEC can classify the image into two classes with unsupervised teaming rule. The proposed method is applied to some experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1321-1325
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• 1993

This paper investigates the use of Fuzzy vector quantizer(FVQ) in speech synthesis. To compress speech data, we employ K-means algorithm to design codebook and then FVQ technique is used to analysize input speech vectors based on the codebook in an analysis part. In FVQ synthesis part, analysis data vectors generated in FVQ analysis is used to synthesize the speech. We have fined that synthesized speech quality depends on Fuzziness values in FVQ, and the optimum fuzziness values maximized synthesized speech SQNR are related with variance values of input speech vectors. This approach is tested on a sentence, and we compare synthesized speech by a convensional VQ with synthesized speech by a FVQ with optimum Fuzziness values.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.777-781
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• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved IAFC model is used to classify the image into two classes. The proposed method is applied to several experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.31-34
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• 1991

This paper presents a voltage-reactive power control algorithm considering fuzziness. In this paper, a coordination technique based on fuzzy set theory is applied for system loss-voltage compromises. Here, we introduce membership functions to measure the adaptability of real power loss of transmission line and the deviation of load bus voltage from the constraints. Then the optimization of problem is solved by a linear programming technique considering the fuzzy set theory. The objective is a degree of satisfaction about the fuzzy decision-making function. The effectiveness of this algorithm has been verified by testing on sample systems.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.50-55
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• 2005

This Paper Presents assessment of fuzzy measure Possibility far the electromagnetic field according to voltage fluctuation of the Jechon Area. To cope with substantial electromagnetic analysis, the safety assessment were analyzed the double 154kV T/L, 345kV T/L, Jechon-Ichon Jechon-Youngju, respectively. As the results of case study, in case of 345kV T/L, the electric field value was 11.4927kV/m, magnetic field value was 0.4622G at the Point about 7m away from the line in severest case. Tn assessment of fuzzy measure Possibility for the electromagnetic field, this paper use probability of fuzzy and measure of fuzziness technique.

• Journal of the Korean Society of Safety
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• v.16 no.3
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• pp.45-52
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• 2001

This paper presents a study on the assessment of fuzzy measure possibility for the electromagnetic field of unbalanced system. It takes into account m untransposed transmission line and unbalanced load. A three phase load flow program was developed which employs a Newton-Raphson method as a tool to analyze system unbalanced. This research presents a method of handling two coupled three phase transmission system unbalance analysis and unbalanced power demand as a function of voltages. In assessment of fuzzy measure possibility for the electromagnetic field, this paper use probability of fuzzy and measure of fuzziness technique.

• Structural Engineering and Mechanics
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• v.3 no.4
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• pp.373-382
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• 1995

The weighting strategy has received a great attention and has been widely applied to multicriterion optimization. This gaper examines a global criterion method (GCM) with the weighting objectives strategy in fuzzy structural engineering problems. Fuzziness of those problems are in their design goals, constraints and variables. Most of the constraints are originated from analysis of engineering mechanics. The GCM is verified to be equivalent to fuzzy goal programming via a truss design. Continued and mixed discrete variable spaces are presented and examined using a fuzzy global criterion method (FGCM). In the design process a weighting parameter with fuzzy information is introduced into the design and decision making. We use a uniform machine-tool spindle as an illustrative example in continuous design space. Fuzzy multicriterion optimization in mixed design space is illustrated by the design of mechanical spring stacks. Results show that weighting strategy in FGCM can generate both the best compromise solution and a set of Pareto solutions in fuzzy environment. Weighting technique with fuzziness provides a more relaxed design domain, which increases the satisfying degree of a compromise solution or improves the final design.

• Journal of the Korean Society of Safety
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• v.21 no.2 s.74
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• pp.22-28
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• 2006

This paper presents assessment of possibility on the human risk for the electromagnetic field of unbalanced two coupled three-phase transmission line using fuzzy theory. Three phase load flow program was developed which employed a Newton-Raphson method as a tool to analyze system unbalanced. This research presents a method of handling two coupled three phase transmission system unbalance analysis and unbalanced power demand as a function of voltages. As the results of case study, in case of 345[kV] T/L, the electric field intensity was 10.9540[kV/m], magnetic field intensity was 0.2567[G] in severest case. The results showed that the membership of a proposition fuzzy '10.9540 [kV/m] is hazardous' is 0.6349. As the analytic results using the fuzzy qualifier term, the membership in case of very false is 0.1379 and fairly false is 0.6124, respectively. In assessment of fuzzy measure possibility for the electromagnetic field, this paper used probability of fuzzy arid measure of fuzziness technique.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.310-315
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• 2004

Image taken in the night can be low-contrast images because of poor environment and image transmission. We propose an algorithm that improves the acquired low-contrast image. MPEG-2 separates chrominance and illuminance, and compresses respectively because human vision is more sensitive to luminance. We extracted illumination and used K-means algorithm to find a proper crossover point automatically. We used K-means algorithm in the viewpoint that the problem of crossover point selection can be considered as the two-category classification problem. We divided an image into two subimages using the crossover point, and applied the histogram equalization method respectively. We used the index of fuzziness to evaluate the degree of improvement. We compare the results of the proposed method with those of other methods.