Proceedings ArticleDOI
Rapid Texture Identification
Kenneth I. Laws
- Vol. 0238, pp 376-381
TLDR
In this article, the texture energy approach requires only a few convolutions with small (typically 5x5) integer coefficient masks, followed by a moving-window absolute average operation.Abstract:
A method is presented for classifying each pixel of a textured image, and thus for segmenting the scene. The "texture energy" approach requires only a few convolutions with small (typically 5x5) integer coefficient masks, followed by a moving-window absolute average operation. Normalization by the local mean and standard deviation eliminates the need for histogram equalization. Rotation-invariance can also be achieved by using averages of the texture energy features. The convolution masks are separable, and can be implemented with 1-dimensional (vertical and horizontal) or multipass 3x3 convolutions. Special techniques permit rapid processing on general-purpose digital computers.read more
Citations
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Texture classification using Curvelet Statistical and Co-occurrence Features
TL;DR: Experimental results show that this approach allows obtaining high degree of success rate in classification of texture classification, and is derived from the sub-bands of the curvelet decomposition.
Journal ArticleDOI
Ovarian Tissue Characterization in Ultrasound: A Review
U. Rajendra Acharya,U. Rajendra Acharya,Filippo Molinari,S. Vinitha Sree,G. Swapna,Luca Saba,Stefano Guerriero,Jasjit S. Suri +7 more
TL;DR: Different types of clinical and nonclinical features that are used to study and analyze the differences between benign and malignant ovarian tumors are discussed.
Proceedings ArticleDOI
Goal-Directed Textured-Image Segmentation
TL;DR: This report concentrates on textured-image segmentation using local texture-energy measures and user delimited training regions to identify regions that are similar to a target texture and dissimilar to other textures.
Texture features for affine registration of thermal (FLIR) and visible images
TL;DR: In this article, texture features are extracted by using texture coefficients and used for fitting registration criterion functions, where a registration criterion function is computed directly from intensity features, i.e. grey values.
Journal ArticleDOI
DIAGNOSIS: A Telematics-Enabled System for Medical Image Archiving, Management, and Diagnosis Assistance
TL;DR: A modular system for medical image archiving, management, diagnosis support, and telematic cooperation is presented, which incorporates a computer-aided diagnosis module aiming at providing support in the diagnosis of focal liver lesions from computed tomography images.
References
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Journal ArticleDOI
Textural Features for Image Classification
TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
ReportDOI
Textured Image Segmentation
TL;DR: In this article, texture energy is measured by filtering with small masks, typically 5x5, then with a moving-window average of the absolute image values, leading to a simple class of texture energy transforms, which perform better than any of the preceding methods.