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Texture Primitive Extraction Using an Edge-Based Approach

TLDR
In this paper, an edge-based procedure for extracting primitives from textures was proposed, which groups edges into region boundaries by joining facing pairs of edge points, and a pilot evaluation was performed by examining the usefulness of these primitives for texture classification.
Abstract
: Many textures are characterizable as a collection of primitive elements arranged over a background field. This paper defines an edge-based procedure for extracting primitives from textures. The technique groups edges into region boundaries by joining facing pairs of edge points. A pilot evaluation is performed by examining the usefulness of these primitives for texture classification. (Author)

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Citations
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Journal ArticleDOI

Texture analysis Anno 1983

TL;DR: The texture analysis methods being used at present are reviewed and statistical as well as structural approaches are included and their performances are compared.
Journal ArticleDOI

Texture Feature Extraction Methods: A Survey

TL;DR: This survey provides a comprehensive survey of the texture feature extraction methods and identifies two classes of methods that deserve attention in the future, as their performances seem interesting, but their thorough study is not performed yet.
Journal ArticleDOI

Texture Classification and Retrieval Using Shearlets and Linear Regression

TL;DR: Novel texture classification and retrieval methods that model adjacent shearlet subband dependences using linear regression and outperform the current state-of-the-art are proposed.
Journal ArticleDOI

SVD-Based Modeling for Image Texture Classification Using Wavelet Transformation

TL;DR: This paper introduces a new model for image texture classification based on wavelet transformation and singular value decomposition that achieves higher recognition rates compared to the traditional subband energy- based approach, the hybrid IMM/SVM approach, and the GGD-based approach.

Image-based transformation of viewpoint and scene appearance

TL;DR: This thesis addresses the problem of synthesizing images of real scenes under threedimensional transformations in viewpoint and appearance and proves that all views on the line segment between the two camera centers are uniquely determined from two uncalibrated views of a scene.
References
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Journal ArticleDOI

Visual Pattern Discrimination

TL;DR: The condition for discrimination was found to be based primarily on clusters or lines formed by proximate points of uniform brightness, and a similar rule of connectivity with hue replacing brightness was obtained by using varicolored dots of equal subjective brightness.
Journal ArticleDOI

Edge and Curve Detection for Visual Scene Analysis

TL;DR: Simple sets of parallel operations are described which can be used to detect texture edges, "spots," and "streaks" in digitized pictures and it is shown that a composite output is constructed in which edges between differently textured regions are detected, and isolated objects are also detected, but the objects composing the textures are ignored.
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Texture Analysis Using Generalized Co-Occurrence Matrices

TL;DR: In this article, a new approach to texture analysis based on the spatial distribution of local features in unsegmented textures is presented, where textures are described using features derived from generalized co-occurrence matrices (GCM).
Journal ArticleDOI

Similarity grouping and peripheral discriminability under uncertainty.

TL;DR: The results support the hypothesis that similarity grouping is a segregative process based on the response of the visual system to stimulus differences before attention narrows or focuses.
Journal ArticleDOI

Computational techniques in the visual segmentation of static scenes

TL;DR: The complexities encountered in applying segmentation techniques to color images of natural scenes involving complex textured objects are analyzed and new ways of using the techniques to overcome some of the problems are explored.