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Handbook of texture analysis /

Texture analysis is one of the fundamental aspects of human vision by which we discriminate between surfaces and objects. In a similar manner, computer vision can take advantage of the cues provided by surface texture to distinguish and recognize objects. In computer vision, texture analysis may be...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Mirmehdi, Majid, Xie, Xianghua, Suri, Jasjit S.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Singapore ; Hackensack, NJ : Imperial College Press ; Distributed by World Scientific, ©2008.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Handbook of texture analysis /  |c edited by Majid Mirmehdi, Xianghua Xie, Jasjit Suri. 
260 |a London :  |b Imperial College Press ;  |a Singapore ;  |a Hackensack, NJ :  |b Distributed by World Scientific,  |c ©2008. 
300 |a 1 online resource (x, 413 pages) :  |b illustrations (some color) 
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504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
505 0 |a Preface; Contents; Chapter 1 Introduction to Texture Analysis E.R. Davies; 1.1. Introduction -- The Idea of a Texture; 1.2. A Simple Texture Analysis Technique and Its Limitations; 1.3. Autocorrelation and Fourier Methods; 1.4. Grey-Level Co-Occurrence Matrices; 1.5. The Texture Energy Approach; 1.6. The Eigenfilter Approach; 1.7. Appraisal of the Texture Energy and Eigenfilter Approaches; 1.8. Problems with Texture Segmentation; 1.9. An X-Ray Inspection Application; 1.9.1. Further details of the algorithm; 1.10. Other Approaches to Texture Analysis; 1.10.1. Fractal-based measures of texture. 
505 8 |a 1.10.2. Markov random field models of texture1.10.3. Structural approaches to texture analysis; 1.10.4. 3D shape from texture; 1.10.5. More recent developments; 1.11. Concluding Remarks; Acknowledgements; References; Chapter 2 Texture Modelling and Synthesis R. Paget; 2.1. Introduction; 2.1.1. Texture perception; 2.2. Texture Analysis; 2.3. Texture Synthesis Modelling; 2.4. Milestones in Texture Synthesis; 2.4.1. Popat and Picard, '93: Novel cluster-based probability model for texture synthesis, classi cation, and compression. 43. 
505 8 |a 2.4.2. Heeger and Bergen, '95: Pyramid based texture analysis/synthesis402.4.3. De Bonet, '97: Multiresolution sampling procedure for analysis and synthesis of texture images39; 2.4.4. Zhu, Wu, and Mumford, '97, '98: FRAME: Filters, random elds and maximum entropy towards a uni ed theory for texture modelling46,47; 2.4.5. Simoncelli and Portilla, '98: Texture characterisation via joint statistics of wavelet coe cient magnitudes48; 2.4.6. Paget and Longsta, '98: Texture synthesis via a nonparametric Markov random eld model20. 
505 8 |a 2.4.7. Efros and Leung, '99: Texture synthesis by non-parametric sampling492.4.8. Wei and Levoy, '00: Fast texture synthesis using tree-structured vector quantisation50; 2.4.9. Zhu, Liu and Wu, '00: Julesz ensemble51; 2.4.10. Xu, Guo and Shum, '00: Chaos mosaic: fast and memory e cient texture synthesis53 and Y.Q. Xu, S.C. Zhu, B.N. Guo, and H.Y. Shum, '01 \Asymptotically Admissible Texture Synthesis""54; 2.4.11. Liang et al., '01: Real-time texture synthesis by patch-based sampling55; 2.4.12. Ashikhmin, '01: Synthesising natural textures56. 
505 8 |a 2.4.13. Hertzmann et al., '01 Image analogies: A general texture transfer framework572.4.14. Efros and Freeman, '01: Image quilting: stitch together patches of input image, texture transfer58; 2.4.15. Zelinka and Garland, '02: Towards Real-Time Texture Synthesis with the Jump Map59; 2.4.16. Tong et al., '02: Synthesis of bidirectional texture functions on arbitrary surfaces61; 2.4.17. Nealen and Alexa, '03: Hybrid texture synthesis62; 2.4.18. Kwatra et al., '03: Graphcut textures: Image and video synthesis using graph cuts64; 2.5. Further Developments; 2.6. Summary; References. 
520 |a Texture analysis is one of the fundamental aspects of human vision by which we discriminate between surfaces and objects. In a similar manner, computer vision can take advantage of the cues provided by surface texture to distinguish and recognize objects. In computer vision, texture analysis may be used alone or in combination with other sensed features (e.g. color, shape, or motion) to perform the task of recognition. Either way, it is a feature of paramount importance and boasts a tremendous body of work in terms of both research and applications. Currently, the main approaches to texture ana. 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Computer vision. 
650 0 |a Visual texture recognition. 
650 6 |a Vision par ordinateur. 
650 6 |a Reconnaissance optique des textures. 
650 7 |a SCIENCE  |x Nanoscience.  |2 bisacsh 
650 7 |a Computer vision  |2 fast 
650 7 |a Visual texture recognition  |2 fast 
650 7 |a Maschinelles Sehen  |2 gnd 
650 7 |a Texturanalyse  |2 gnd 
655 4 |a Aufsatzsammlung. 
655 7 |a Aufsatzsammlung.  |2 swd 
700 1 |a Mirmehdi, Majid. 
700 1 |a Xie, Xianghua. 
700 1 |a Suri, Jasjit S. 
776 0 8 |i Print version:  |t Handbook of texture analysis.  |d London : Imperial College Press ; Singapore ; Hackensack, NJ : Distributed by World Scientific, ©2008  |z 9781848161153  |w (DLC) 2009275474  |w (OCoLC)213479529 
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