• Title/Summary/Keyword: Gabor wavelet

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Identification of Mass-lines and Rigid Body Properties Using Wavelet Transform (웨이블렛 변환을 이용한 질량선 및 강체특성의 규명)

  • 안세진;정의봉;황대선
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.12 no.9
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    • pp.725-730
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    • 2002
  • The rigid body properties of a structure may be estimated easily if the mass-line of the structure could be taken exactly. However, the exact mass-line nay be hard to be obtained exactly in experiments. The mass line value can be read from the mass line in frequency response function. However, the mass lines in the frequency response function sometimes show the fluctuation with frequency, and it cannot be read correctly. In this paper, the wavelet transform is applied to obtain the good mass line value. The mass line calculated by using wavelet transform has unique value and showed in the range of fluctuated values of frequency response function. The rigid body properties obtained by wavelet transform also showed better results than those by fourier transform.

Image Retrieval using VQ based Local Modified Gabor Feature (변형된 지역 Gabor Feature를 이용한 VQ 기반의 영상 검색)

  • Shin, Dae-Kyu;Kim, Hyun-Sool;Park, Sang-Hui
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.2634-2636
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    • 2001
  • This paper proposes a new method of retrieving images from large image databases. The method is based on VQ(Vector Quantization) of local texture information at interest points automatically detected in an image. The texture features are extracted by Gabor wavelet filter bank, and rearranged for rotation. These features are classified by VQ and then construct a pattern histogram. Retrievals are performed by just comparing pattern histograms between images. Experimental results have shown the robustness of the proposed method to image rotation, small scale change, noise addition and brightness change and also shown the possibility of the retrieval by a partial image.

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Image Forgery Detection Using Gabor Filter (가보 필터를 이용한 이미지 위조 검출 기법)

  • NININAHAZWE, Sheilha;Rhee, Kyung-Hyune
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.11a
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    • pp.520-522
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    • 2014
  • Due to the availability of easy-to-use and powerful image editing tools, the authentication of digital images cannot be taken for granted and it gives rise to non-intrusive forgery detection problem because all imaging devices do not embed watermark. Forgery detection plays an important role in this case. In this paper, an effective framework for passive-blind method for copy-move image forgery detection is proposed, based on Gabor filter which is robust to illumination, rotation invariant, robust to scale. For the detection, the suspicious image is selected and Gabor wavelet is applied from whole scale space and whole direction space. We will extract the mean and the standard deviation as the texture features and feature vectors. Finally, a distance is calculated between two textures feature vectors to determine the forgery, and the decision will be made based on that result.

Human Iris Recognition using Wavelet Transform and Neural Network

  • Cho, Seong-Won;Kim, Jae-Min;Won, Jung-Woo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.178-186
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    • 2003
  • Recently, many researchers have been interested in biometric systems such as fingerprint, handwriting, key-stroke patterns and human iris. From the viewpoint of reliability and robustness, iris recognition is the most attractive biometric system. Moreover, the iris recognition system is a comfortable biometric system, since the video image of an eye can be taken at a distance. In this paper, we discuss human iris recognition, which is based on accurate iris localization, robust feature extraction, and Neural Network classification. The iris region is accurately localized in the eye image using a multiresolution active snake model. For the feature representation, the localized iris image is decomposed using wavelet transform based on dyadic Haar wavelet. Experimental results show the usefulness of wavelet transform in comparison to conventional Gabor transform. In addition, we present a new method for setting initial weight vectors in competitive learning. The proposed initialization method yields better accuracy than the conventional method.

The Robust Derivative Code for Object Recognition

  • Wang, Hainan;Zhang, Baochang;Zheng, Hong;Cao, Yao;Guo, Zhenhua;Qian, Chengshan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.1
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    • pp.272-287
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    • 2017
  • This paper proposes new methods, named Derivative Code (DerivativeCode) and Derivative Code Pattern (DCP), for object recognition. The discriminative derivative code is used to capture the local relationship in the input image by concatenating binary results of the mathematical derivative value. Gabor based DerivativeCode is directly used to solve the palmprint recognition problem, which achieves a much better performance than the state-of-art results on the PolyU palmprint database. A new local pattern method, named Derivative Code Pattern (DCP), is further introduced to calculate the local pattern feature based on Dervativecode for object recognition. Similar to local binary pattern (LBP), DCP can be further combined with Gabor features and modeled by spatial histogram. To evaluate the performance of DCP and Gabor-DCP, we test them on the FERET and PolyU infrared face databases, and experimental results show that the proposed method achieves a better result than LBP and some state-of-the-arts.

Age of Face Classification based on Gabor Feature and Fuzzy Support Vector Machines (Gabor 특징과 FSVM 기반의 연령별 얼굴 분류)

  • Lee, Hyun-Jik;Kim, Yoon-Ho;Lee, Joo-Shin
    • Journal of Advanced Navigation Technology
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    • v.16 no.1
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    • pp.151-157
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    • 2012
  • Recently, owing to the technology advances in computer science and image processing, age of face classification have become prevalent topics. It is difficult to estimate age of facial shape with statistical figures because facial shape of the person should change due to not only biological gene but also personal habits. In this paper, we proposed a robust age of face classification method by using Gabor feature and fuzzy support vector machine(SVM). Gabor wavelet function is used for extracting facial feature vector and in order to solve the intrinsic age ambiguity problem, a fuzzy support vector machine(FSVM) is introduced. By utilizing the FSVM age membership functions is defined. Some experiments have conducted to testify the proposed approach and experimental results showed that the proposed method can achieve better age of face classification precision.

Image Denoising of Human Visual Filter Using GCST (GCST를 이용한 인간시각필터의 영상 잡음 제거)

  • Lee, Juck-Sik
    • Journal of the Institute of Convergence Signal Processing
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    • v.9 no.4
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    • pp.253-260
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    • 2008
  • Image denoising as one of image enhancement methods has been studied a lot in the spatial and transform domain filtering. Recently wavelet transform which has an excellent energy compaction and a property of multiresolution has widely used for image denoising. But a transform based on human visual system is visually useful if an end user is human beings. Therefore, Gabor cosine and sine transform which is considered as human visual filter is applied to image denoising areas in this paper. Denoising performance of the proposed transform is compared with those of the derivatives of Gaussian transform being another human visual filter and of discrete wavelet transform in terms of PSNR. With three levels of various noises, experimental results for real images show that the proposed transform has better PSNR performance of 0.41dB than DWT and 0.14dB than DGT.

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A study on the Quality Assessment Method on Railway Video Transmission System (철도영상전송시스템의 화질평가방안에 관한 연구)

  • Chang Seok-Gahk;Cho Bong-Kwan
    • Proceedings of the KSR Conference
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    • 2004.10a
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    • pp.1247-1252
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    • 2004
  • A objective quality assessment for the evaluation performance of a video transmission system as a basic step for construction of digital video transmission system between the spots and headquarter. Due to a limit of an analog video transmission system and the developments of various digital media and digital video standards, the need of introduce of a digital system are increased gradual1y, At this points. previously performance evaluations are performed and the quality assessment is the most important thing. We can be divided quality assessment method by the subjective quality assessment and objective quality assessment. The subjective quality assessment method has some problems which are required high cost and much time to evaluate the quality, And because existing objective quality assessment method such that PSNR are based on an analog form, the correlation with subjective data is very low. Therefore we design a new objective quality assessment method using Gabor wavelet transform reflecting HVS(Human Visual System), Designed objective quality assessment method is superior to other objective method such that PSNR or EPSNR In this paper, we proposed objective quality assessment using Gabor wavelet can be used for performance evaluation and verification of video transmission system.

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Feature Variance and Adaptive classifier for Efficient Face Recognition (효과적인 얼굴 인식을 위한 특징 분포 및 적응적 인식기)

  • Dawadi, Pankaj Raj;Nam, Mi Young;Rhee, Phill Kyu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2007.11a
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    • pp.34-37
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    • 2007
  • Face recognition is still a challenging problem in pattern recognition field which is affected by different factors such as facial expression, illumination, pose etc. The facial feature such as eyes, nose, and mouth constitute a complete face. Mouth feature of face is under the undesirable effect of facial expression as many factors contribute the low performance. We proposed a new approach for face recognition under facial expression applying two cascaded classifiers to improve recognition rate. All facial expression images are treated by general purpose classifier at first stage. All rejected images (applying threshold) are used for adaptation using GA for improvement in recognition rate. We apply Gabor Wavelet as a general classifier and Gabor wavelet with Genetic Algorithm for adaptation under expression variance to solve this issue. We have designed, implemented and demonstrated our proposed approach addressing this issue. FERET face image dataset have been chosen for training and testing and we have achieved a very good success.

Adaptive Facial Expression Recognition System based on Gabor Wavelet Neural Network (가버 웨이블릿 신경망 기반 적응 표정인식 시스템)

  • Lee, Sang-Wan;Kim, Dae-Jin;Kim, Yong-Soo;Bien, Zeungnam
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.1
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    • pp.1-7
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    • 2006
  • In this paper, adaptive Facial Emotional Recognition system based on Gabor Wavelet Neural Network, considering six feature Points in face image to extract specific features of facial expression, is proposed. Levenberg-Marquardt-based training methodology is used to formulate initial network, including feature extraction stage. Therefore, heuristics in determining feature extraction process can be excluded. Moreover, to make an adaptive network for new user, Q-learning which has enhanced reward function and unsupervised fuzzy neural network model are used. Q-learning enables the system to ge optimal Gabor filters' sets which are capable of obtaining separable features, and Fuzzy Neural Network enables it to adapt to the user's change. Therefore, proposed system has a good on-line adaptation capability, meaning that it can trace the change of user's face continuously.