• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.635-638
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• 2006

현재 인공위성 영상은 지구에서 일어나는 변화를 탐지하기 위한 매우 효율적 수단으로 활용되고 있다. 지표에 대한 변화탐지는 원격탐사영상으로부터 지표변화를 찾아내 정량화하는 과정이 필요한데 이러한 정보를 추출하기 위해 본 연구에서는 웨이블렛을 이용한 텍스쳐 분석의 효율성이 연구되었다. 분석된 영상은 0.6m급 고해상도 위성영상으로 지진 전후로 하여 지진피해 지역을 탐지하기 위해 영상에서 관찰되는 풍부한 텍스쳐 정보를 활용하는 방법에 관한 연구가 이루어 졌다. 텍스쳐 특징을 추출하기 위해 GLCM이 이용되었는데 직접적인 GLCM의 적용보다는 웨이블렛변환 후 GLCM의 적용이 텍스쳐 특징을 보다 효과적으로 분리할 수 있는 방법임이 검사되었다. 이러한 웨이블렛 텍스쳐 특징 추출 후 상관관계에 기반한 변화탐지 기법을 적용하면 피해지역을 매핑할 수 있다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.185-188
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• 2003

본 논문은 복합적인 상황을 고려한 데이터를 이용하여 얼굴인식을 하는 연구로서, 이산 웨이블렛을 기반으로 하는 다 해상도 분석 방법을 사용하고, 각 해상도로 분해된 영상 중, 스케일 함수에 의해 사영되어진 영역에 LDA(Linear Discriminant Analysis)를 적용하여, 도출된 결과가 기존의 방법들에 비해 더 안정된 성능을 나타냄을 보이고자 한다. 이를 위해, 웨이블렛을 적용하지 않은 이미지에 PCA, LDA, ICA를 이용한 결과와 웨이블렛을 적용한 이미지에 통계적 방법들을 이용한 경우, 그리고 웨이블렛의 각 대역에 통계적인 방법을 적용한 후, 대수적인 합을 하였을 때의 인식율을 학습과 검증의 이미지배열을 바꾸어 가며 총 열여덟회 실험하였다. 이에, 본 논문에서 제안한 방법이 이미지 배열에 영향을 덜 받는 안정적인 성능을 가지고 있음을 확인 할 수 있었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.769-773
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• 2008

• Korea Multimedia Society
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• v.7 no.2
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• pp.9-15
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• 2003

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.403-409
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• 2007

Contourlet transform is an extention of the wavelet transform in two dimensions using the multiscale and directional fillet banks. The contourlet transform has the advantages of multiscale and time-frequency-localization properties of wavelets, but also provides a high degree of directionality. In this paper, we propose a face recognition system based on fusion methods using contourlet transform and PCA. After decomposing a face image into directional subband images by contourlet, features are obtained in each subband by PCA. Finally, face recognition is performed by fusion technique that effectively combines similarities calculated respectively In each local subband. To show the effectiveness of the proposed method, we performed experiments for ORL and CBNU dataset, and then we obtained better recognition performance in comparison with the results produced by conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2317-2328
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• 1997

The objective of this paper is to develop an algorithm for a real-time automatic fingerprint recognition system. The algorithm employs the wavelet transform(WT) and the dominat local orientation that derived from the gradient Gaussian(GoG) and coherence in determining the directions of ridges in fingerprint images. By using the WT, the algorithm does not require conventional preprocessing procedures such as smothing, binarization, thining and restoration. For recognition, two fingerprint images are compared in three different ST domains;one that represents the original image compressed to quarter(LL), another that shows vertical directional characteristic(LH), and third as the block that contains horizontal direction(HL) in WT domain. Each block has dominat local orientation that derived from the GoG and coherence. The proposed algorithm is imprlemented on a SunSparc-2 workstation under X-window environment. Our simulation results, in real-time have shown that while the rate of Type II error-Incorrect recognition of two identical fingerprints as the identical fingerprints-is held at 0%, the rate of Type I error-Incorrect recognitionof two identical fingerprints as the different ones-is 2.5%.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.150-155
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• 2004

In this paper, an emotion recognition method using speech signal is presented. Six basic human emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. The proposed recognizer have each codebook constructed by using the wavelet transform for the emotional state. Here, we first verify the emotional state at each filterbank and then the final recognition is obtained from a multi-decision method scheme. The database consists of 360 emotional utterances from twenty person who talk a sentence three times for six emotional states. The proposed method showed more 5% improvement of the recognition rate than previous works.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.291-294
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• 2007

비디오 시스템으로 영상 획득하는 과정에서 다양한 조명상태는 얼굴인식에 있어서 심각한 영향을 준다. 본 논문에서는 웨이블렛 변환을 이용하여 영상을 나눈 후 각각의 영역에 얼굴영상을 인식에 알맞은 조명상태로 변환한다. 변환과정은 얼굴을 히스토그램 지정연산으로 명암에 대해 개선과 경계부분을 강화하여 얼굴인식을 위한 영상을 만들어 인식률을 높였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.175-179
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• 2007

To existing method which uses energy variation and spectrum deviation to detect the underwater transient signal is useful to detect white noise environment, but it is not useful to do colored noise environment. To improve capacity of detecting the underwater transient signal both in white noise environment and colored noise environment, this study takes advantage of Double Density Discrete Wavelet Transform and CFAR Power-Law.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.3
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• pp.159-166
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• 2007

This paper evaluates the soundness of structural elements using Wavelet Packet Transform (WPT). WPT is applied to the response acceleration of a framed structure which is subjected to earthquake load to decompose the response acceleration, then the energy of each component is calculated. The first five largest components in energy magnitude among the decomposed components are selected as input to an ANN to identify the damage location and severity. Two nodes in output layer yield damaged element and damage severity respectively. This method successfully evaluates the amount of damage and its location in the structure.