| 000 | 01211namuu22003378a 4500 | |
| 001 | 000000822213 | |
| 005 | 20030725104806 | |
| 008 | 020620s2002 nyua b 001 0 eng | |
| 010 | ▼a 2026662 | |
| 020 | ▼a 038795547X (alk. paper) | |
| 040 | ▼a DLC ▼c DLC ▼d OHX ▼d 211009 | |
| 041 | 1 | ▼a eng ▼h fre |
| 042 | ▼a pcc | |
| 049 | 1 | ▼l 121081600 ▼f 과학 |
| 050 | 0 0 | ▼a QA1 ▼b .A647 ▼a TA1637 |
| 072 | 7 | ▼a TA ▼2 lcco |
| 082 | 0 0 | ▼a 006.4/2 ▼2 21 |
| 090 | ▼a 006.42 ▼b C438m | |
| 100 | 1 | ▼a Chalmond, Bernard, ▼d 1951- |
| 240 | 1 0 | ▼a Elements de modelisation pour l'analyse d'images. ▼l English |
| 245 | 1 0 | ▼a Modeling and inverse problems in image analysis / ▼c Bernard Chalmond. |
| 260 | ▼a New York : ▼b Springer, ▼c 2002. | |
| 263 | ▼a 0212 | |
| 300 | ▼a xxii,309 p. : ▼b ill. ; ▼c 24 cm. | |
| 490 | 1 | ▼a Applied mathematical sciences ; ▼v 155 |
| 504 | ▼a Includes bibliographical references and index. | |
| 650 | 0 | ▼a Image processing ▼x Digital techniques ▼x Mathematical models. |
| 650 | 0 | ▼a Image analysis ▼x Mathematical models. |
| 650 | 0 | ▼a Inverse problems (Differential equations) |
| 830 | 0 | ▼a Applied mathematical sciences (Springer-Verlag New York Inc.) ; ▼v v. 155. |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 006.42 C438m | 등록번호 121081600 (2회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
More mathematicians have been taking part in the development of digital image processing as a science and the contributions are reflected in the increasingly important role modeling has played solving complex problems. This book is mostly concerned with energy-based models. Most of these models come from industrial projects in which the author was involved in robot vision and radiography: tracking 3D lines, radiographic image processing, 3D reconstruction and tomography, matching, deformation learning. Numerous graphical illustrations accompany the text.
Translated by Kari A. Foster.
More mathematicians have been taking part in the development of digital image processing as a science and the contributions are reflected in the increasingly important role modeling has played solving complex problems. This book is mostly concerned with energy-based models. Through concrete image analysis problems, the author develops consistent modeling, a know-how generally hidden in the proposed solutions. The book is divided into three main parts. The first two parts describe the materials necessary to the models expressed in the third part. These materials include splines (variational approach, regression spline, spline in high dimension), and random fields (Markovian field, parametric estimation, stochastic and deterministic optimization, continuous Gaussian field). Most of these models come from industrial projects in which the author was involved in robot vision and radiography: tracking 3D lines, radiographic image processing, 3D reconstruction and tomography, matching, deformation learning. Numerous graphical illustrations accompany the text showing the performance of the proposed models. This book will be useful to researchers and graduate students in applied mathematics, computer vision, and physics.
New feature
More mathematics have been taking part in the development of digital image processing as a science, and the contributions are reflected in the increasingly important role modeling has played solving complex problems. This book is mostly concerned with energy-based models. Through concrete image analysis problems, the author develops consistent modeling, a know-how generally hidden in the proposed solutions.
The book is divided into three main parts. The first two parts describe the theory behind the applications that are presented in the third part. These materials include splines (variational approach, regression spline, spline in high dimension) and random fields (Markovian field, parametric estimation, stochastic and deterministic optimization, continuous Gaussian field). Most of these applications come from industrial projects in which the author was involved in robot vision and radiography: tracking 3-D lines, radiographic image processing, 3-D reconstruction and tomography, matching and deformation learning. Numerous graphical illustrations accompany the text showing the performance of the proposed models.
This book will be useful to researchers and graduate students in mathematics, physics, computer science, and engineering.
정보제공 :
목차
Acknowledgments List of Figures Notation and Symbols Introduction I Spline Models Non-parametric spline models Parametric spline models Auto-Associative Models II Markov Models Fundamental Aspects Bayesian estimation Simulation and optimization Parameter Estimation III Modeling in Action Model-building Degradation in Imaging Detection of filamentary Entities Reconstruction and Projections Matching References
정보제공 :