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2014 Journal of Computer Science  
The classification results were compared with curvelet transform features and wavelet packet features.  ...  Images were normalized and plaque regions have been manually segmented by experts and these Region Of Interests (ROI) have been used for further processing. 4 level Contourlet transform has been applied  ...  SVM and probabilistic neural network classifiers were used for classifying carotid plaques (Tsiaparas et al., 2011) .  ... 
doi:10.3844/jcssp.2014.1642.1649 fatcat:xjtdhln44facthkdgp6eigq6dm

Detection and Classification Brain Tumor of Magnetic Resonance Imaging Using 2D Gabor Wavelet Transform and Artificial Neural Network: A Review

S.A. Nagtode, Bhakti B Potdukhe
2015 International Journal of IT-based Public Health Management  
Artificial neural network use for the Automated and accurate classification of MRI images of brain tumor.  ...  Probabilistic Neural Network gives proper result of classification than other artificial neural networks and it is a optimistic tool for classification of the brain Tumors .  ...  Detection of tumor using 2D Gabor wavelet transform and classification of tumor using artificial neural network (ANN).  ... 
doi:10.21742/ijiphm.2015.2.2.02 fatcat:5b7qyqkt2zbnponwzdvhbuu66q

Face detection using quantized skin color regions merging and wavelet packet analysis

C. Garcia, G. Tziritas
1999 IEEE transactions on multimedia  
Constraints related to shape and size of faces are applied, and face intensity texture is analyzed by performing a wavelet packet decomposition on each face area candidate in order to detect human faces  ...  The wavelet coefficients of the band filtered images characterize the face texture and a set of simple statistical deviations is extracted in order to form compact and meaningful feature vectors.  ...  Liapis for the implementation of the color quantization algorithm, and the INA's Innovation Department and ERT Television for having provided test video materials.  ... 
doi:10.1109/6046.784465 fatcat:iizuoofmlbbrpa3pkkoasfs7de

Wavelets in industrial applications: a review

Frederic Truchetet, Olivier Laligant, Frederic Truchetet, Olivier Laligant
2004 Wavelet Applications in Industrial Processing II  
and discrete wavelet transform proceeding with image processing and applications.  ...  After a quick recall in a simple overview of the basics of wavelet transform and of its main variations, some of its applications are reviewed domain by domain, beginning with signal processing, continuous  ...  D. 130 , how WT and probabilistic neural network can help to achieve such an analysis in real time.  ... 
doi:10.1117/12.580395 fatcat:zxitt2wsvvcwnjzyrtuhppdb2e

Comparison of Multiresolution Features for Texture Classification of Carotid Atherosclerosis From B-Mode Ultrasound

N Tsiaparas, S Golemati, I Andreadis, J S Stoitsis, I Valavanis, K S Nikita
2011 IEEE Transactions on Information Technology in Biomedicine  
The selected features were subsequently input into two classifiers using support vector machines (SVM) and probabilistic neural networks.  ...  Four decomposition schemes, namely, the discrete wavelet transform, the stationary wavelet transform, wavelet packets (WP), and Gabor transform (GT), as well as several basis functions, were investigated  ...  Probabilistic neural networks (PNN) and support vector machines (SVM), both recently used for the classification of morphological features of carotid atherosclerotic plaque [15] , were used as classifiers  ... 
doi:10.1109/titb.2010.2091511 pmid:21075733 fatcat:byumhz6ymbcs7lh3vujtfavtwm

Search for Resolution Invariant Wavelet Features of Melanoma Learned by a Limited ANN Classifier

Grzegorz Surówka
2017 Schedae Informaticae  
Features used for our classification experiments are derived from wavelet decomposition coefficients of the image.  ...  We present back-propagated Artificial Neural Network (ANN) classifiers discriminating dermoscopic skin lesion images into two classes: malignant melanoma and dysplastic nevus.  ...  Preprocessing of dermoscopic images through the Fourier and log-polar transforms was used to build an unsupervised image segmentation and image registration system where neural networks and discriminant  ... 
doi:10.4467/20838476si.16.015.6196 fatcat:sjbynzccfjhrlgnjs7y3umdwcu

Speaker Recognition System Based on Wavelet Features and Gaussian Mixture Models

2019 International Journal of Engineering and Advanced Technology  
In this work, an efficient method for speaker recognition is made by using Discrete Wavelet Transform (DWT) features and Gaussian Mixture Models (GMM) for classification is presented.  ...  Results show a better accuracy of 96.18% speaker signals using DWT features and GMM classifier  ...  The classification is made by radial basis function neural network models, probabilistic neural network and general regressive neural network.  ... 
doi:10.35940/ijeat.a3069.109119 fatcat:xcqppwwcnvayne3knk4uoky5j4

Automatic Character Recognition in Complex Images

Anju K Sadasivan, T. Senthilkumar
2012 Procedia Engineering  
Manual assignment of text data from images is time consuming and costly. Hence automation of text extraction from images is a challenging area in image processing due to its potential applications.  ...  Some of these applications include character recognitions in surveillance, object identification, banking sector, market survey and all..  ...  Then nonlinear transform function is applied on the wavelet packet coefficients for obtaining a better representation of natural textured images and hence the wavelet packet coefficients become quantized  ... 
doi:10.1016/j.proeng.2012.01.854 fatcat:yzzglc4g6jdrfpltseudop6see

Multimodal Biometrics Based on Fingerprint and Finger Vein

Anand Viswanathan, S. Chitra
2014 Research Journal of Applied Sciences Engineering and Technology  
Feature selection is through PCA and kernel PCA. Classification is achieved through KNN, Naïve Bayes and RBF Neural Network Classifiers.  ...  For fingerprint images, energy coefficients are attained using wavelet packet tree. Both features are normalized using min max normalization and fused with concatenation.  ...  Feature selection is by using PCA and kernel PCA. Classification is through use of KNN, Naïve Bayes and RBF Neural Network Classifiers.  ... 
doi:10.19026/rjaset.8.964 fatcat:i6qmizoqv5bavoupdi674eryti

An Evolutionary Algorithm for Enhanced Magnetic Resonance Imaging Classification

T.S. Murunya, S. Audithan
2014 Research Journal of Applied Sciences Engineering and Technology  
Image processing techniques are required to analyze medical images and retrieve it from database. The proposed framework extracts features using Moment Invariants (MI) and Wavelet Packet Tree (WPT).  ...  This study presents an image classification method for retrieval of images from a multi-varied MRI database.  ...  The second stage fine-tuned classification using Neural Network (NN) by making feature subset elicited in first stage network inputs.  ... 
doi:10.19026/rjaset.8.1205 fatcat:a5ni43eazjdffnu7vn3rbaozom

Identification of Carotid Asymptomatic Plaque Using Texture and Orientation Features for Health Care

D. Sasikala, M. Madheswaran
2014 Research Journal of Applied Sciences Engineering and Technology  
The plaque region has been segmented using cubic spline interpolation method for multiresolution analysis using discrete wavelet transform.  ...  The carotid artery asymptomatic plaque identification has been done using the texture features at various orientation scales and presented in this study.  ...  The Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT), Wavelets Packets (WP) and Gabor transform were used to decompose the carotid plaque.  ... 
doi:10.19026/rjaset.8.940 fatcat:seuotyrhdzb6perr4fjfinkrce

Texture recognition by generalized probabilistic decision-based neural networks

Yeong-Yuh Xu, C.-L. Tseng, Hsin-Chia Fu
2011 Expert systems with applications  
Keywords: Bayesian decision-based neural networks Generalized probabilistic decision-based neural networks GPDNN Texture recognition Supervised learning a b s t r a c t Texture recognition have received  ...  Based on a two-layer pyramid-type network structure, the proposed GPDNN receives texture data via 2-D grid input nodes, and outputs the classification and/or retrieval results at the top layer node.  ...  Kung and Prof. Y.H. Hu for their helpful suggestions regarding the probabilistic DBNN and statistical pattern recognition methods.  ... 
doi:10.1016/j.eswa.2010.11.051 fatcat:oqw653kgkvbk3fksjd24mtzvni

Review of industrial applications of wavelet and multiresolution-based signal and image processing

Frédéric Truchetet
2008 Journal of Electronic Imaging (JEI)  
Twenty five years after the seminal work of Jean Morlet, the wavelet transform, multiresolution analysis, and other spacefrequency or space-scale approaches are considered standard tools by researchers  ...  in image processing.  ...  If the Fourier transform is currently used to analyze distorted waves in the frequency domain, Tsao 164 has shown how the WT and probabilistic neural network can help to achieve such an analysis in real  ... 
doi:10.1117/1.2957606 fatcat:eat5xpexendmtcyjlli7zo2glu

A Survey on Various Defect Detection

Rashmi Mishra, Ms. Dolly Shukla
2014 International Journal of Engineering Trends and Technoloy  
variety of colors, textures, and sizes so it's a good option for many environments.  ...  In this paper, we are going to review various defect detection methods to detecting the defects from different types of images which are used in automated visual Inspection System and also compare all  ...  Artificial neural networks find their application in pattern recognition (classification, clustering, feature selection), texture analysis, segmentation, image compression, color representation and several  ... 
doi:10.14445/22315381/ijett-v10p329 fatcat:ylm73vjennfg5iv2fapls6upou

Retinal Image Analysis Using Morphological Process and Clustering Technique

Radha R, Bijee Lakshman
2013 Signal & Image Processing An International Journal  
In this system we use the Probabilistic Neural Network (PNN) for training and testing the pre-processed images.  ...  The contrast image is enhanced by curvelet transform. Hence, morphology operators are applied to the enhanced image in order to find the retinal image ridges.  ...  but the method used here is in conjunction with the discrete wavelet transform in which wavelet packet transform -an extension of discrete wavelet transform is used and found that the computation complexity  ... 
doi:10.5121/sipij.2013.4605 fatcat:h57rmkuz7rh6rddux45iaciw3m
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