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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Patent
Sensor arrangement for the detection of specimen containers
Ethan Montag,Richard Geisler +1 more
TL;DR: In this paper, a sensor arrangement for the detection of sample bodies in a sensing range with an image sensor having optical sensor at first end of detection range and with textured background at a second end of the detection range is described.
Journal ArticleDOI
Using Radiomics-Based Machine Learning to Create Targeted Test Sets to Improve Specific Mammography Reader Cohort Performance: A Feasibility Study
TL;DR: In this article , a radiomics-based machine learning pipeline focusing on global radiomic features was proposed to predict false positive and false negative errors in mammography reading, which can be used to develop group-tailored mammographic educational strategies to improve future mammography reader performance.
Aνάπτυξη αλγορίθμου αυτόματης κατάτμησης εικόνων καρωτίδας από υπερήχους EΘNIKO METΣOBIO ΠOΛYTEXNEIO
Proceedings ArticleDOI
Characterization of IR sea clutter
TL;DR: In this paper , a search for features that seem useful for discriminating between different levels of sea clutter is performed, such as texture energy measures, properties of the Fourier coefficients, and statistical features of segments in a thresholded image.
Book ChapterDOI
Anisotropic Diffusion-Based Color Texture Analysis for Industrial Application
TL;DR: This chapter proposes the framework for computer vision algorithm for industrial application, which uses wavelet transform to obtain the multiresolution images and Linear discriminant analysis is employed to get the distinguished features.
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.