A Taxonomy for Texture Description and Identification (Springer Series in Perception Engineering)

Rao, A. Ravishankar

ISBN 10: 1461397790 / ISBN 13: 9781461397793

Editore: Springer, 2012

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Codice articolo ria9781461397793_new

Dati bibliografici

• Titolo: A Taxonomy for Texture Description and Identification (Springer Series in Perception Engineering)
• Editore: Springer
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 1461397790
• ISBN 13: 9781461397793
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

This book solves the signal to symbol transformation problem for texture, an important issue in computer vision. The algorithms developed here have been applied to a wide variety of textured images.

Contenuti

1 Introduction.- 1.1 Scope of the book.- 1.1.1 Defining texture.- 1.1.2 Problem definition.- 1.2 Importance of texture.- 1.3 Potential applications of this research.- 1.4 Issues in automated process control involving computer vision.- 1.4.1 Background.- 1.4.2 Problems involving texture.- 1.4.3 The desired solution.- 1.5 A taxonomy for texture.- 1.6 Outline.- 2 Computing oriented texture fields.- 2.1 Introduction.- 2.2 Background.- 2.3 Oriented Texture Fields.- 2.4 Experimental Methods.- 2.4.1 A best estimate for dominant local orientation.- 2.4.2 Derivation using the moment method.- 2.4.3 Squaring the Gradient Vectors: Kass and Witkin’s scheme.- 2.4.4 Inverse Arctangent.- 2.4.5 Flow Orientation Coherence.- 2.4.6 The effect of varying ?1 on the estimate of dominant orientation.- 2.5 Experimental Results.- 2.5.1 Comparing Calculations for Orientation.- 2.5.2 Comparing Measures of Coherence.- 2.6 Analyzing texture at different scales.- 2.7 Processing of the intrinsic images.- 2.7.1 The coherence intrinsic image.- 2.7.2 The angle intrinsic image.- 2.8 Conclusions.- 3 The analysis of oriented textures through phase portraits.- 3.1 Introduction.- 3.1.1 Overview of approach.- 3.2 Background.- 3.2.1 Related Research.- 3.2.2 Potential Applications.- 3.2.3 Obtaining the intrinsic images.- 3.2.4 Problems in post-processing.- 3.3 Geometric theory of differential equations.- 3.3.1 Preliminary definitions.- 3.3.1.1 One dimensional case.- 3.3.1.2 Two dimensional case.- 3.3.2 Linear systems.- 3.3.2.1 Case 1: Matrix A is non-singular.- 3.3.2.2 Case 2: Matrix A is singular.- 3.3.2.3 Affine transformations.- 3.3.3 Relevance of the theory.- 3.3.4 The perceptual significance of flow-like patterns.- 3.4 Experimental Methods.- 3.4.1 A Distance Measure.- 3.4.2 Non-linear least squares fitting.- 3.4.3 Implementation details.- 3.4.3.1 Generating the orientation field O2.- 3.4.3.2 Normalization of orientation fields.- 3.4.3.3 Uniqueness of the solution.- 3.4.3.4 Real Images.- 3.4.4 Segmentation.- 3.4.4.1 A measure for closeness of fit.- 3.4.4.2 Selecting the size of the window.- 3.4.5 Locating fixed points.- 3.4.6 Reconstructing the original texture.- 3.5 Experimental Results.- 3.5.1 Flow past an inclined plate.- 3.5.2 Image of secondary streaming.- 3.5.3 Image of wood knots.- 3.5.4 Image of complex flow.- 3.5.5 Image of vortex flow.- 3.5.6 Analysis of a resist gel defect.- 3.5.7 Analysis of textured paint brush strokes.- 3.6 Experiments with noise addition.- 3.7 A related model from fluid flow analysis.- 3.7.1 A comparison between the fluid motion viewpoint and the phase portrait viewpoint.- 3.7.2 Classification of velocity fields.- 3.7.3 Importance of divergence and curl.- 3.8 Discussion.- 3.8.1 Extensions to three dimensions.- 3.9 Conclusion.- 4 Analyzing strongly ordered textures.- 4.1 Introduction.- 4.2 Extraction of primitives.- 4.2.1 Edge based features.- 4.2.2 Region based features.- 4.2.2.1 Thresholding the response to ?2G.- 4.2.2.2 Solving for the response to a disk at multiple scales.- 4.3 Extracting structure from primitives.- 4.3.1 Syntactic approaches.- 4.3.2 Nearest Neighbor Histograms.- 4.3.3 Using co-occurrence matrices.- 4.3.4 Graph based approaches.- 4.4 Models for strongly ordered textures.- 4.4.1 Directions for further research.- 4.5 Symbolic descriptions: models from petrography.- 4.5.1 Description of primitives.- 4.5.1.1 Terminology from petrology.- 4.5.2 Description of placement of primitives.- 4.6 Frieze groups and wallpaper groups.- 4.6.1 Background.- 4.6.2 Preliminary definitions.- 4.6.3 Frieze groups.- 4.6.4 Wallpaper groups.- 4.7 Implications for computer vision.- 4.8 Summary.- 5 Disordered textures.- 5.1 Statistical measures for disordered textures.- 5.1.1 Computing the entropy as a measure for disorder.- 5.2 Describing disordered textures by means of the fractal dimension.- 5.2.1 Advantages.- 5.3 Computing the fractal dimension.- 5.3.1 Using the expected values of intensity differences.- 5.3.2 The reticular cell counting method for computing the fractal dimension.- 5.3.3 A comparison of the methods for measuring fractal dimension.- 5.4 Experimental Results.- 5.4.1 Implementation results for computing the entropy as a measure for disorder.- 5.4.2 Using the expected values of intensity differences.- 5.4.3 Reticular cell counting method for the fractal dimension.- 5.4.4 Discussion of results.- 5.5 Conclusion.- 6 Compositional textures.- 6.1 Introduction.- 6.2 Primitive textures.- 6.3 A Parametrized symbol set.- 6.4 Three types of composition.- 6.5 Linear combination (transparent overlap).- 6.6 Functional composition.- 6.6.1 W ? S.- 6.6.2 D ? S.- 6.6.3 D ? W.- 6.6.4 W ? D.- 6.6.5 S ? D.- 6.6.6 S ? W.- 6.6.7 S ? S, D ? D and W ? W.- 6.7 Opaque overlap.- 6.8 Definition of texture.- 6.9 A complete taxonomy for texture.- 6.10 Implementing the taxonomy.- 6.10.1 Operators for texture.- 6.10.2 Sequencing of the operators.- 6.11 Conclusion.- 7 Conclusion.- 7.1 Summary of results.- 7.1.1 Analysis of weakly ordered textures.- 7.1.2 Strongly Ordered Textures.- 7.1.3 Disordered Textures.- 7.1.4 Compositional Textures.- 7.2 Contributions.- 7.3 Future Work.- 7.3.1 Application to inspection problems.- 7.3.2 An automatic texture interpretation scheme.- 7.3.3 Taxonomies for other visual cues.- 7.3.4 Improving algorithms for Oriented Texture Analysis.- B Region Refinement.- C Preparation of the manuscript.- Permissions.