Textural Features
Forged Image Detection by Analyzing Edge, Visual Saliency and Textural Features using SVM Classifier
... Nowadays, the use of Digital images is everywhere, in the magazines, in newspapers, in hospitals, in shopping malls and all over the Internet. As the development in technology is increasing day by day, at the same time ...
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Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors
... ADC textural features, separately or in combination, neither yielded useful classification performance nor improved further ADC histogram metrics-based perfor- ...Shape, textural, and histogram ...
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Creating a Optimal Set of Textural Features for Cervical Cancer Lesions Using Hierarchal Clustering Technique
... An image is described has what it is by the features it processes. It can be used to describe what the image actually is. Here we have taken into consideration four different classes of textural ...
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A Study on Morphological and Textural Features for Classifying Breast Lesion in Ultrasound Images
... discriminating features in CAD is a most prominent task that results in good ...Morphological features and thirty eight Textural features (six Histogram, fourteen GLCM, eleven GLRLM, Fractal ...
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Implementing textural features on GPUs for improved real time pavement distress detection
... the textural features, HAWCP is a reliable pavement distress detection feature in most ...only textural features were considered, a detection of distress in the images would still be possible ...
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Radiomics in paediatric neuro oncology : MRI textural features as diagnostic and prognostic biomarkers
... It may be argued that the use of a cohort of 48 subjects is rather small given the number of textural features used, which can potentially lead to fitting instability or over-fitting. We therefore ...
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Egocentric Activity Recognition using Histogram Oriented Features and Textural Features
... oriented features like Histogram of Oriented Gradients (HOG), Histogram of optical Flow (HOF) and Motion Boundary Histogram (MBH) and textural features like Gray Level co-occurrence Matrix (GLCM) and ...
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HMM based Offline Signature Verification system using ContourletTransform and Textural features
... directional features and Hidden Markov Model (HMM) as ...The textural features are computed and concatenated with coefficients of contourlet transform to form the final feature ...
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Determining Optimal Textural Features for Cervical Cancer lesions using the Gaussian Function
... of features to determine whether the given cell is cancerous or ...many features then the accuracy goes up but speed comes ...the features it is the other way ...of features which can be used ...
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Textural Features and Feature Selection in KAN NADA Character Recognition
... The features used in the classifier are obtained from the directional information of contour points of the ...directional features are computed in each of the ...and features obtained from the down ...
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Texture Feature Representation and Retrieval
... a textural features because, from the user perspective, it can be useful as for users it has a perceptual meaning different from coarseness (regardless of the way we estimate ...the textural ...
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Textural Analysis of Spinous Layer for Grading Oral Submucous Fibrosis
... epithelium. Textural features are extracted by using wavelet decomposition of the ...ROI. Features’ distribution and significance are estimated by using Jarque- Bera test, boxplot, one-way ANOVA ...
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Texture Classification using Artificial Neural Network for Diagnosis of Skin Cancer
... of textural descriptors to localize the abnormal visual attributes which may appear in the tested skin tissue ...the textural features extracted from training samples were analyzed and their ...
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Automated classification of dense calcium tissues in gray-scale intravascular ultrasound images using a deep belief network
... selected features re- vealed similar classification results for 10-fold cross val- idation, and we found a significant reliability for these textural ...
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Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture Based Machine Learning
... MATERIALS AND METHODS: Seventy-one adult patients with enhancing gliomas and 35 adult patients with primary central nervous system lymphomas were included. The tumors were manually contoured on contrast-enhanced T1WI, ...
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Application of image texture analysis for varietal classification of barley
... The features calculated using first-order statistics of an image are not textural features because they depend only on the inten- sity of individual pixels, and they are independent of the adjacent ...
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Spectropathology-corroborated multimodal quantitative imaging biomarkers for neuroretinal degeneration in diabetic retinopathy
... and textural features of the retinal layers, whereas geometric features of the retinal vasculature were extracted from fun- doscopy and ...texture-based features extracted from the retinal ...
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Multiple Representations of Perceptual Features for Texture Classification and Retrieval
... perceptual features to distinguish between textured images or ...Perceptual features are highly desirable for two reasons; they will be optimum in terms of feature selection and will be applicable to all ...
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Real Time Face Detection and Road Sign Detection for Blind People using Open CV
... fourteen textural features of GLCM, which includes Angular 2nd second, evaluation, Correlation, Sum of squares, Inverse distinction moment, sum of average, Sum variance, Sum Entropy, difference Variance, ...
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Efficient CAD system based on GLCM& derived feature for diagnosing Breast Cancer
... the textural features derived from GLCM and also validate the efficiency of new texture defined by us in the ...GLCM textural features ...
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