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A comparison study to evaluate retinal image enhancement techniques

A comparison study to evaluate retinal image enhancement tec...

引用

IEEE International conference on signal and image processing applications (ICSIPA)

作者： Mohammad Saleh Miri Ali Mahloojifar Biomedical Engineering Department Tarbiat Moalem University Tehran Iran

Retinal vessels can show different states of several diseases, making the detection of vessels in retinal images very crucial. Retinal images can be used for other applications such as ocular fundus operations and human recognition. Due to the acquisition process, these images often have low grey level contrast and dynamic range that can seriously affect diagnosis procedure results. In this paper, we present an algorithm for retinal image contrast enhancement based on the second generation of new multi-resolution analysis tool called Curvelet Transform which is faster and simpler than the first version. Curvelet transform has favorable geometric features that provide better representation of edges compare to other widely used multi-resolution tools such as wavelet. We use a nonlinear function to modify the Curvelet coefficients based on their statistic features. Results of applying this method to a known database, DRIVE, and comparing with previous approaches, proved this method to be effective and helpful for image segmentation.

关键词： Retina image enhancement Retinal vessels Diseases Humans image recognition Dynamic range image analysis Algorithm design and analysis wavelet transforms

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PDF based face recognition system in different colour channels using discrete wavelet decomposition

PDF based face recognition system in different colour channe...

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IEEE signal processing and Communications applications (SIU)

作者： Gholamreza Anbarjafari Hasan Demirel Elektrik ve Elektronik Muhendislii Bolumu Dogu Akdeniz Universitesi Turkey

In this paper, a new high performance face recognition system based on the probability distribution functions of pixels obtained from intensity images in HSI and YCbCr colour channels and their decomposed images obtained by discrete wavelet decomposition is proposed. The PDFs of the equalized face images in spatial and subband domains in different colour channel are used as statistical feature vectors for the recognition of faces by minimizing the Kullback- Leibler Distance between the PDF of a given face and the PDFs of faces in the database. Majority voting and feature vector fusion methods have been employed to combine feature vectors obtained from different colour channels to improve the recognition performance.

关键词： Face recognition Discrete wavelet transforms Probability distribution Pixel image recognition image databases Spatial databases Voting Principal component analysis Linear discriminant analysis

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A Neural Network based system for Persian sign language recognition

A Neural Network based system for Persian sign language reco...

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IEEE International conference on signal and image processing applications (ICSIPA)

作者： Azadeh Kiani Sarkaleh Fereshteh Poorahangaryan Bahman Zanj Ali Karami Faculty of Engineering University of Guilan Rasht Iran

This paper presents a static gesture recognition system for recognizing some selected words of Persian sign language (PSL). The required images for the selected words are obtained using a digital camera. The color images are first resized, and then converted to grayscale images. Then, the discrete wavelet transform (DWT) is applied on the selected images and some features are extracted. Finally, a multi layered Perceptron (MLP) Neural Network (NN) is trained to classify the selected images. Our recognition system does not use any gloves or visual marking systems. The system was implemented and tested using a data set of 240 samples of Persian sign images; 30 images for each sign. The experiments show that the proposed system is able to classify the selected PSL signs with a classification accuracy of 98.75% when the network is trained using MATLAB NN Toolbox.

关键词： Neural networks Handicapped aids Discrete wavelet transforms Digital cameras Color image converters Gray-scale Feature extraction Data mining System testing

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Generalized Ridgelet-Fourier for M×N images: Determining the normalization criteria

Generalized Ridgelet-Fourier for M×N images: Determining th...

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IEEE International conference on signal and image processing applications (ICSIPA)

作者： Mas Rina Mustaffa Fatimah Ahmad Ramlan Mahmod Shyamala Doraisamy Faculty of Computer Science and Information Technology Department of Multimedia Universiti Putra Malaysia Serdang Selangor Darul Ehsan Malaysia

Ridgelet transform (RT) has gained its popularity due to its capability in dealing with line singularities effectively. Many of the existing RT however is only applied to images of size M×M or the M×N images will need to be pre-segmented into M×M sub-images prior to processing. The research presented in this article is aimed at the development of a generalized RT for content-based image retrieval so that it can be applied easily to any images of various sizes. This article focuses on comparing and determining the normalization criteria for Radon transform, which will aid in achieving the aim. The Radon transform normalization criteria sets are compared and evaluated on an image database consisting of 216 images, where the precision and recall and Averaged Normalized Modified Retrieval Rank (ANMRR) are measured.

关键词： wavelet transforms image retrieval Application software Content based retrieval signal processing image processing Computer science Information technology image representation image denoising

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Fusion Segmentation Algorithm for SAR images Based on HMT in Contourlet Domain and D-S Theory of Evidence

Fusion Segmentation Algorithm for SAR Images Based on HMT in...

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International conference on Computational Science and Its applications (ICCSA 2009)

作者： Wu, Yan Li, Ming Zong, Haitao Wang, Xin Xidian Univ Sch Elect Engn Xian 710071 Peoples R China Xidian Univ Natl Key Lab Radar signal processing Xian 710071 Peoples R China

ISBN: (纸本)9783642024566

Utilizing the Contourlet's advantages of multiscale, localization, directionality and anisotropy, a new SAR image segmentation algorithm based on hidden Markov tree (HMT) in Contourlet domain and dempster-shafer (D-S) theory of evidence is proposed in this paper. The algorithm extends the hidden Markov tree framework to Contourlet domain and fuses the clustering and persistence of Contourlet transform using HMT model and D-S theory, and then, we deduce the maximum a posterior (MAP) segmentation equation for the new fusion model. The algorithm is used to segment the real SAR images. Experimental results and analysis show that the proposed algorithm effectively reduces the influence of multiplicative speckle noise, improves the segmentation accuracy and provides a better visual quality for SAR images over the algorithms based on HMT-MRF in the wavelet domain. HMT and MRF in the Contourlet domain, respectively.

关键词： SAR images segmentation Contourlet transform hidden Markov tree (HMT) D-S theory of evidence

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Phase Properties of Complex wavelet Coefficients

Phase Properties of Complex Wavelet Coefficients

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International conference on Innovative Computing, Information and Control (ICICIC)

作者： Guo-Rui Zhou Wen-Jiang Wang Shi-Xin Sun School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China Department of Engineering Longcheer Company Limited Shanghai China

The importance of phase in signal processing has been known for a long time. This paper presents an overview to the recent advances in phase properties of CWT coefficients. Our attention is mainly put on describing phase properties based on theoretical analyses and experimental results. The applications of the phase properties are briefly introduced. At last, we give an conclusion and an outlook.

关键词： wavelet coefficients Continuous wavelet transforms wavelet transforms Discrete wavelet transforms Computer science Hidden Markov models Fourier transforms Sun signal processing image processing

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A novel max-plus algebra based wavelet transform and its applications in image processing

A novel max-plus algebra based wavelet transform and its app...

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IEEE International conference on Systems, Man and Cybernetics

作者： Barnabás Bede Hajime Nobuhara Department of Mathematics University of Texas-Pan American Edinburgh TX UK Department Intelligent Interaction and Technologies University of Tsukuba Tsukuba Ibaraki Japan

Max-plus algebra based wavelet transforms are considered currently to be the world's fastest image processing methods. In the present paper a novel max-plus algebra based wavelet transform is proposed and studied both from the theoretical and practical points of view. The novel MP-wavelets considered here employ strictly neighbor pixels in the calculations and their most important properties are: very low computational complexity, flexible sampling window size and potentially, very easy hardware implementation.

关键词： Algebra wavelet transforms image processing Mathematics USA Councils Computational complexity Hardware Morphology Surveillance signal generators

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image Denoising using Contourlet Transform

Image Denoising using Contourlet Transform

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International conference on Computer and Electrical Engineering, ICCEE

作者： R. Sivakumar G. Balaji R.S.J. Ravikiran R. Karikalan S. Saraswathi Janaki ECE Department RMK Engineering College Kavaraipettai Tamilnadu India

In image processing, considering fields like remote sensing and medical applications, speckle (Multiplicative) noise dominates which affects the valuable features and important information of the image. To denoise an image, various transforms are used. But they are not efficient in case of preserving the edges which is the important factor in image processing for image denoising. In this paper we have used the new algorithm based on the transformation named "contourlet transform". This algorithm is more efficient than the wavelet algorithm in image denoising particularly for the removal of speckle noise. The parameters considered for comparing the wavelet and contourlet transforms are SNR and IEF. The results show that this proposed algorithm outperforms the wavelet in terms of SNR, IEF values and visual perspective as well.

关键词： image denoising Speckle Discrete transforms Filter bank wavelet transforms Band pass filters image processing signal to noise ratio Noise reduction Laplace equations

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Automatic power quality disturbance measurement in distribution systems

Automatic power quality disturbance measurement in distribut...

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IEEE International conference on signal and image processing applications (ICSIPA)

作者： Sudipta Nath Aritra Dasgupta Department of Applied Electronics and Instrumentation Engineering Netaji Subhash Engineering College Kolkata West Bengal India

An automatic power quality disturbance measurement system has been proposed in this paper. The probabilistic entropy is calculated for the most frequently occurring short duration disturbances in distribution system which is based on Shannon's entropy. The variation of probabilistic entropy with respect to the deviation in the magnitude and duration of the disturbed signal is presented in the form of bar chart and graphs. The automatic recognition is achieved using an artificial neural network, (ANN) in conjunction with fuzzy based decision logic. A new type of power quality (PQ) factor, Equivalent Disturbance Factor (EDF) has been proposed in this paper. Then ANN has been implemented to predict the Equivalent Disturbance Factor.

关键词： Power quality Power measurement Artificial neural networks Power engineering and energy Entropy signal processing Neural networks Fuzzy neural networks wavelet transforms Feeds

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Palmprint recognition with applying different kernel matrix sizes on Gabor wavelet features

Palmprint recognition with applying different kernel matrix ...

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IEEE signal processing and Communications applications (SIU)

作者： Murat Aykut Murat Ekinci Bilgisayarla Goru Lab. Bilgisayar Muhendisligi Bolumu Karadeniz Teknik Universitesi Turkey

This paper presents Gabor based Kernel Principal Component Analysis (KPCA) palmprint recognition method for human identification. The intensity values of palmprint images extracted by using an image preprocessing method are first normalized. Then these images are transformed to the spectral domain by using Gabor wavelet transform. The transformed palm images exhibit strong characteristics of spatial locality, scale, and orientation selectivity. Next, the feature vectors are nonlinearly maps into a high dimensional feature space with KPCA method. In this method during kernel matrix calculation, the sample numbers per class changed and it's effect investigated. Finally, weighted Euclidean distance based nearest neighbor method is realized for classification. The proposed algorithm tested on the most-well known palmprint database, PolyU, includes 7752 samples of 386 different people.

关键词： Kernel Principal component analysis Humans wavelet domain wavelet transforms Euclidean distance Nearest neighbor searches Classification algorithms Testing Spatial databases

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