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Gabor wavelet feature vectors

Texture Image Classification Using Visual Perceptual Texture Features and Gabor Wavelet Features

Texture Image Classification Using Visual Perceptual Texture Features and Gabor Wavelet Features

... and Gabor wavelet ...on Gabor wavelet features are normally used to construct feature vectors for texture image ...effective Gabor wavelet subbands based on ...

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Analysis of Image Retrieval Using Linear Transformation Techniques

Analysis of Image Retrieval Using Linear Transformation Techniques

... techniques Gabor-Walsh Wavelet pyramid technique and Curvelet transform 7method Feature vectors of each of the database images are extracted by applying these techniques, then by calculating ...

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Improved Approaches Edge Direction Histogram and HSV Histogram, Color Auto Correlagram; Gabor Wavelet Transforms using CBIR

Improved Approaches Edge Direction Histogram and HSV Histogram, Color Auto Correlagram; Gabor Wavelet Transforms using CBIR

... vector. Feature vectors are supplied for ant colony optimization (ACO) function selection which selects the most relevant ...and feature collection technique) by 2% and 1% with deference to precision ...

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Face Representation Using Combined Method of Gabor Filters, Wavelet Transformation and DCV and Recognition Using RBF

Face Representation Using Combined Method of Gabor Filters, Wavelet Transformation and DCV and Recognition Using RBF

... augmented Gabor feature vector derived from the Gabor wavelet representation of face images to obtain a low- dimensional feature representation with enhanced dis- crimination ...

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UNSUPERVISED SEGMENTATION OF TEXTURE IMAGES USING A COMBINATION OF GABOR AND WAVELET FEATURE

UNSUPERVISED SEGMENTATION OF TEXTURE IMAGES USING A COMBINATION OF GABOR AND WAVELET FEATURE

... of Gabor filters or dyadic discrete wavelet ...The feature vectors computed from the local energy measure estimates are local mean and local variance, which represent local texture ...These ...

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Human Facial Expression Recognition using Gabor Filter Bank with Minimum Number of Feature Vectors

Human Facial Expression Recognition using Gabor Filter Bank with Minimum Number of Feature Vectors

... The Gabor filter produces two parts: the real part and the imaginary ...of Gabor feature: the magnitude and phase. There are 40 Gabor feature for each ...image. Gabor ...

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Facial Feature Expression Based Approach For Human Face Recognition: A Review

Facial Feature Expression Based Approach For Human Face Recognition: A Review

... M represents the mouth feature. The distance between the two eyes is w and the distance from the mouth to the eyes is h. In frontal face images, structural relationships such as the Euclidean distance between the ...

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Classification of breast tissue in mammograms using efficient coding

Classification of breast tissue in mammograms using efficient coding

... Wei [5] investigated the feasibility of using multiresolution texture analysis for differ- entiation of masses from normal breast tissue on mammograms and use texture features based on the wavelet coefficients and ...

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PHOTOGRAPH RETRIEVAL BASED ON FACE SKETCH USING SIFT WITH PCA

PHOTOGRAPH RETRIEVAL BASED ON FACE SKETCH USING SIFT WITH PCA

... Feature extraction is the most widely used feature description technique in appearance based face recognition methods. Despite its poor generalization abilities in unconstrained scenarios, it is being used ...

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Facial Expression Recognition Using Multiresolution Analysis

Facial Expression Recognition Using Multiresolution Analysis

... vision, feature representation is the process of generating useful information from the images/image sequences/videos, such that, effective use of the information can be robust enough to categorize the images into ...

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Performance Enhancement of Facial Expression Recognition using Appearance based features

Performance Enhancement of Facial Expression Recognition using Appearance based features

... of Gabor wavelet parameters for natural ...a Gabor filter after that Gabor features are down sampled and dimensions of feature vector were reduced using ...

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Introduction To Palmprint Recognition

Introduction To Palmprint Recognition

... complex Gabor wavelet transform ...complex Gabor wavelet and the values of theta are loaded in the feature ...The feature vector is matched by hamming distance similarity ...

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Classification of Soil Image using Feature Extraction

Classification of Soil Image using Feature Extraction

... This process is adjusting digital images because of this suitable for display result. Image analysis is called Image Enhancement. Spatial domain method and frequency domain method is two category of method enhancement. ...

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Performance Analysis of Security and Accuracy on Palmprint Based Biometric Authentication System

Performance Analysis of Security and Accuracy on Palmprint Based Biometric Authentication System

... based feature extraction methods exist to extract the lines from Palmprint image like Sobel [15], Phase congruency [7, 10], Canny ...based feature extraction is to accurately extract the line features, as ...

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FACE RECOGNITION USING GABOR WAVELET TRANSFORM AND FEED FORWARD NEURAL NETWORK

FACE RECOGNITION USING GABOR WAVELET TRANSFORM AND FEED FORWARD NEURAL NETWORK

... 2D Gabor wavelet transform, the local information is extracted from the nodes of a predefined graph, leaving some details on a face which is useful in detection ...using Gabor wavelet ...

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Gabor Convolutional Networks

Gabor Convolutional Networks

... to Gabor filters (see the filters highlighted by yellow boxes in the left column of ...of Gabor filters are widely adopted in the traditional filter design due to their enhanced capability of scale and ...

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Comparison and Fusion of Multiresolution Features for Texture Classification

Comparison and Fusion of Multiresolution Features for Texture Classification

... dyadic wavelet transform, the texture image regions are decomposed with 3 levels, and db1, db4, db8, coif1, and coif4 basis are ...the wavelet frame transform, the setup is the same to the dyadic ...

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Classification of Power Quality Disturbances Using  Wavelet Packet Energy Entropy and LS SVM

Classification of Power Quality Disturbances Using Wavelet Packet Energy Entropy and LS SVM

... the wavelet detail at each level is, in addition to decomposition of only the wavelet approxi- mation in the regular wavelet analysis, further decom- posed in to its own approximation and detail ...

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Adaptive Lifting Transform for Classification of Hyperspectral Signatures

Adaptive Lifting Transform for Classification of Hyperspectral Signatures

... Weighted Feature Extraction (NWFE) algorithm by Kuo and Landgrebe gives 92% accuracy using Gaussian classifier with 12 features and 50 training samples of each ...

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Volume 3, Issue 2, February 2014 Page 238

Volume 3, Issue 2, February 2014 Page 238

... characteristic feature images called ‘Eigenfaces’, which are actually the principal components of the initial training set of face ...important feature of PCA is that one can reconstruct any original image ...

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