Recent years have seen dramatic progress in shape recognition algorithms applied to ever-growing image databases. They have been applied to image stitching, stereo vision, image mosaics, solid object recognition and video or web image retrieval. More fundamentally, the ability of humans and animals to detect and recognize shapes is one of the enigmas of perception. The book describes a complete method that starts from a query image and an image database and yields a list of the images in the database containing shapes present in the query image. A false alarm number is associated to each detection. Many experiments will show that familiar simple shapes or images can reliably be identified with false alarm numbers ranging from 10-5 to less than 10-300. Technically speaking, there are two main issues. The first is extracting invariant shape descriptors from digital images. Indeed, a shape can be seen from various angles anddistances and in various lights. Jean-Michel Morel belongs to the ISI list ofhighly cited mathematicians (http://isihighlycited.com/) The theory presentedis new and original The text aims at being self-contained in all three aspects: mathematics, vision and algorithms Specialists in image analysis and computer vision find the text easy on the computer vision side and affordable on themathematical level INDICE: 1.Introduction.- Part I Extracting Image boundaries: 2.Extracting Meaningful Curves from Images.- Part II Level Line Invariant Descriptors: 3.Robust Shape Directions.- 4.Invariant Level Line Encoding.- Part III RecognizingLevel Lines: 5.A Contrario Decision: the LLD Method.- 6.Meaningful Matches: Experiments on LLD and MSER.- Part V The SIFT Method: 10.The SIFT Method.- 11.Securing SIFT with A Contrario Techniques.- A.Keynotes.- A.1.Cluster Analysis Reader’s Digest.- A.2.Three classical methods for object detection based on spatial coherence.- A.3.On the Negative Association of Multinomial Distributions.- B.Algorithms.- B.1.LLD Method Summary.- B.2.Improved MSER Method Summary.- B.3.Improved SIFT Method Summary.- References.- Index.
- ISBN: 978-3-540-68480-0
- Editorial: Springer
- Encuadernacion: Rústica
- Páginas: 270
- Fecha Publicación: 01/07/2008
- Nº Volúmenes: 1
- Idioma: Inglés