Mathematical Morphology and Its Applications to Image and Signal ProcessingJohn Goutsias, Luc Vincent, Dan S. Bloomberg Mathematical morphology is a powerful methodology for the processing and analysis of geometric structure in signals and images. This book contains the proceedings of the fifth International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing, held June 26-28, 2000, at Xerox PARC, Palo Alto, California. It provides a broad sampling of the most recent theoretical and practical developments of mathematical morphology and its applications to image and signal processing. Areas covered include: decomposition of structuring functions and morphological operators, morphological discretization, filtering, connectivity and connected operators, morphological shape analysis and interpolation, texture analysis, morphological segmentation, morphological multiresolution techniques and scale-spaces, and morphological algorithms and applications. Audience: The subject matter of this volume will be of interest to electrical engineers, computer scientists, and mathematicians whose research work is focused on the theoretical and practical aspects of nonlinear signal and image processing. It will also be of interest to those working in computer vision, applied mathematics, and computer graphics. |
Contents
Shape Analysis and Interpolation | 71 |
Filtering | 97 |
Connectivity and Connected Operators | 139 |
Flooding and Segmentation | 189 |
A Morphological MultiScale Gradient for Color Image Segmentation | 199 |
Automatic Watershed Segmentation of Color Images | 207 |
Motion Segmentation using Seeded Region Growing | 215 |
A Segmentation Pyramid for the Interactive Segmentation of | 223 |
Partition Lattice Operators for Extraction of Semantic Video Objects | 233 |
Texture Analysis | 243 |
Surface Texture Classification from Morphological Transformations | 253 |
Testing Some Morphological Approaches to Face Localization | 415 |
Quantitative Description of Telecommunication Networks by Simula | 425 |
A De Jesus and J Facon | 433 |
| 435 | |
Other editions - View all
Mathematical Morphology and Its Applications to Image and Signal Processing John Goutsias,Luc Vincent,Dan S. Bloomberg No preview available - 2013 |
Mathematical Morphology and Its Applications to Image and Signal Processing John Goutsias,Luc Vincent,Dan S. Bloomberg No preview available - 2000 |
Common terms and phrases
affine affine transformation algorithm approach binary image bounded space catchment basins color images complete lattice compute connected components connectivity class consider convex corresponding criterion curve decomposition defined definition denoted detection dilation distance distance transform edge equation erosion example extraction Figure flat zones flooding fuzzy geodesic given gradient grayscale grey level Hausdorff discretization Heijmans hierarchical idempotent IEEE Transactions image analysis Image Processing infimum input interpolation invariant level lines linear logo markers Mathematical Morphology merging method metric minima minimum Minkowski Minkowski addition mipmap morphological filters morphological operators motion multiscale node objects obtained original image parameters partial ordering partition path pixel problem proposed Proposition pyramid queue reconstruction regions representation sampling scale scale-space segmentation sequence Serra Signal Processing structuring element structuring function subset supremum techniques texture Theorem threshold topology transform tree vector watershed watershed algorithm