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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Automated analysis of MR image of hip: geometrical evaluation of the Legg-Calve-Perthes disease.
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Stratified squamous epithelial biopsy image classifier using machine learning and neighborhood feature selection
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Texture description using different wavelet transforms based on statistical parameters
TL;DR: In this paper, the success rates of Haar, Daubechies-6 and Coiflet-6 wavelet transforms are estimated based on first-order statistics on the entire image.
Book ChapterDOI
A Genetic Algorithm-Based Level Set Curve Evolution for Prostate Segmentation on Pelvic CT and MRI Images
TL;DR: A novel genetic algorithm is presented here that performs level set curve evolution using texture and shape information to automatically segment the prostate on pelvic images in computed tomography and magnetic resonance imaging modalities.
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.