• Proceedings of the KIEE Conference
• /
• 2004.11b
• /
• pp.293-296
• /
• 2004

This paper proposes a new protective relaying algorithm using ACI(Advanced Computational Intelligence) and wavelet transform. To organize the advanced neuro-fuzzy algorithm, it is important to select target data reflecting various transformer transient states. These data are made of changing-rates of D1 coefficient and RSM value within half cycle after fault occurrence. Subsequently, the advanced neuro-fuzzy algorithm is obtained by converging the target data. As a result of applying the advanced neuro-fuzzy algorithm, discrimination between internal fault and inrush is correctly distinguished within half cycle after fault occurrence. Accordingly, it is evaluated that the proposed algorithm can effectively protect a transformer by correcting discrimination between winding fault and inrushing state.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.10a
• /
• pp.697-699
• /
• 2001

본 논문에서는 웨이블릿(wavelet) 계수간의 시각특성을 이용만 새로운 블라인더 워터마킹 기법을 제안 한다. 각 대역별 시각특성을 고려한 워터마크 삽입으로 원 영상의 손실을 최소화하였다. 그리고 여러 영상 처리에 대해 지속적인 관계를 유지하는 계수간의 특성을 이용하여 모든 주파수 대역에 위터마크를 삽입함으로써 강인성을 높였다. 워터마크 추출 시에는 삽입과정에서 이용된 계수간의 상황관계를 이용하여 원 영상 없이도 워터마크를 추출할 수 있다. 실험결과, 제안한 방법의 워터마킹 영상들은 PSNR 측정결과 약 38dB로 비교적 우수함을 보였으며 시각적으로도 손상을 감지하기 어려웠다. 또한, 강인성 검증을 위한 손실압축, 클리핑, 블러링, 샤프닝 등의 영상 변경 후 워터마크 추출에서도 기존방법에 비해 상대적으로 우수한 검출 결과를 보였다.

• Journal of the Korea Society of Computer and Information
• /
• v.6 no.4
• /
• pp.21-29
• /
• 2001

We show that image make converts of multiplex resolution using wavelet transform algorithm. To evaluate the robustness. we have measured comparison or similarity using various sequences which is inserted important coefficient of middle frequency band. The wavelet transform is advantage that it has a special quality of frequency domain and a special quality of spatial domain. Watermark is used pseudo random number, gaussian sequence, chaos sequence and sobel sequence. As result of experiments, it is to certify that The chaos sequence similarity is higher than other sequence. So the chaos sequence will be used for watermark sequence.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.2
• /
• pp.415-419
• /
• 2007

Data compression is very important for the storage and transmission of informations. EZW image compression algorithm has been widely used in real application due to its high compression performance. In the EZW algorithm, when a new significant coefficient is generated, its children are all encoded, although its all descendants may be insignificant, and thus its performance is declined. In this paper, we proposed an improved EZW algorithm using IS(Isolated Significant) symbol, which checks all descendants of significant coefficient and avoids encoding the children of each newly generated significant coefficient if it has no significant descendant.

• Journal of Korea Water Resources Association
• /
• v.45 no.12
• /
• pp.1321-1330
• /
• 2012

In this study, the daily inflow at the basin of Chungju dam is predicted using wavelet-artificial neural network for nonlinear model. Time series generally consists of a linear combination of trend, periodicity and stochastic component. However, when framing time series model through these data, trend and periodicity component have to be removed. Wavelet transform which is denoising technique is applied to remove nonlinear dynamic noise such as trend and periodicity included in hydrometeorological data and simple noise that arises in the measurement process. The wavelet-artificial neural network (WANN) using data applied wavelet transform as input variable and the artificial neural network (ANN) using only raw data are compared. As a results, coefficient of determination and the slope through linear regression show that WANN is higher than ANN by 0.031 and 0.0115 respectively. And RMSE and RRMSE of WANN are smaller than those of ANN by 37.388 and 0.099 respectively. Therefore, WANN model applied in this study shows more accurate results than ANN and application of denoising technique through wavelet transforms is expected that more accurate predictions than the use of raw data with noise.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.22 no.4
• /
• pp.26-34
• /
• 2008

This study focus on segmentation process that classifies road surfaces into 5 different categories, dry, wet water, icy, and snowy surfaces by analyzing asphalt-paved road images taken in daylight. By using the polarization coefficients, the proportions of horizontally polarized components to vertically polarized components, regions with over 1.3 polarization coefficients are classified as wet surfaces. Except for wet surfaces, the decision process a lies time-frequency analysis to other parts by using the third order wavelet packet transform. In addition, by using the average frequency characteristics of dry and icy surfaces from image templates, decide which is closer to a test image, and finally identify dry and icy surfaces. It is confirmed that the reposed estimation and segmentation of recognition on various images. This can be interpreted as an indication that image-only mad surface condition supervision is probable.

• Advances in environmental research
• /
• v.6 no.4
• /
• pp.265-279
• /
• 2017

The climate change has made adverse effects on land surface temperature for many regions of the world. Several climatic studies focused on different downscaling techniques for climatological parameters of different regions. For statistical downscaling of any hydrological parameters, conventional Neural Network Models were used in common. However, it seems that in any modeling study, uncertainty is a vital aspect when making any predictions about the performance. In this paper, Gamma Test is performed to determine the data length selection for training to minimize the uncertainty in model development. Another measure to improve the data quality and model development are wavelet transforms. Hence, Gamma Test with Wavelet decomposed Feedforward Neural Network (GT-WNN) model is developed and tested for downscaled land surface temperature of Patna Urban, Bihar. The results of GT-WNN model are compared with GT-FFNN and conventional Feedforward Neural Network (FFNN) model. The effectiveness of the developed models is illustrated by Root Mean Square Error and Coefficient of Correlation. Results showed that GT-WNN outperformed the GT-FFNN and conventional FFNN in downscaling the land surface temperature. The land surface temperature is forecasted for a period of 2015-2044 with GT-WNN model for Patna Urban in Bihar. In addition, the significance of the probable changes in the land surface temperature is also found through Mann-Kendall (M-K) Test for Summer, Winter, Monsoon and Post Monsoon seasons. Results showed an increasing surface temperature trend for summer and winter seasons and no significant trend for monsoon and post monsoon season over the study area for the period between 2015 and 2044. Overall, the M-K test analysis for the annual data shows an increasing trend in the land surface temperature of Patna Urban.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.6
• /
• pp.51-60
• /
• 2003

The watermarking is the technique that embeds or extracts the certain data without the change of the original data for the copyright protection of the multimedia contents. Watermark-embedded contents must not be distinguished by human's eye and must be robust to the various image processing and the intentional distortions. In this paper, we propose a new watermarking technique applied in the wavelet domain which has both the spatial and frequency information of a image. For both the robustness and the invisibility, the positions for embedding the watermark is selected with the multi-threshold. We search the similarity between highly correlated coefficients in the each subband and decide the mark space after verifying the significance in the specified subband. The similarity is represented by the coefficient difference between the subbands and its distribution is used in the watermark embedding and extracting. The embedded watermark can be extracted without the original image using the relationship of the subbands. By these properties the proposed watermarking algorithm has the invisibility and the robustness to the attacks such as JPEG compression and the general image processing.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.8
• /
• pp.48-54
• /
• 1999

A new method for wavelet embedded image coding is presented extending the bases of the Shapiro's algorithm by incorporating edge detection, zerotree scheme, and classified VQ(CVQ). Generally edges in the image are regarded an visually important components and the previous literatures have proved that significant coefficients in wavelet transform domain correspond to the edges in spatial domain. Hence, by identifying the edge elements, the significant coefficient can be easily detected in wavelet domain without investigating descendant coefficients across layer. Hierarchical trees for the significant components are organized, and then CVQ method is applied to these trees. Since the significant information has higher priority in transmission, the simulation shows that our coder provides a superior performance over the conventional method and can be successfully applied to the application areas that require of progressive transmission.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.6
• /
• pp.76-86
• /
• 1999

In this paper, it is shown that the car number plate are segmented and extracted more efficiently by using wavelet transform. A car image is decomposed by wavelet transform, and the high frequency image of the decomposed image are selected as feature images. Three selected feature images are synthesized of a single feature image, and a region including the plate is segmented by the correlation coefficient between the feature image and the synthesized image. For segmented plate region, the car plate region is extracted by deciding the Y-axis region composed by vertical region, the car plate region is extracted by deciding the Y-axis region composed by vertical histogram and the X-axis region composed by the variance histogram. Some experiment results of the various image and shown. It has been shown from the results with the high rate of 96% that the car number plates can be segmented and extracted more extractly and efficiently than converntional method.