Kniha Recognizing Planar Objects Using Invariant Image Features Thomas H. Reiss

Recognizing Planar Objects Using Invariant Image Features

Jazyk: Angličtina
Väzba: Brožovaná
Dostupnosť: Skladom u dodávateľa
Odosielame za 5-8 dní
47.04
Given a familiar object extracted from its surroundings, we§humans have little difficulty in recogni...

Informácie o knihe

Jazyk
Angličtina
Väzba
Kniha - Brožovaná
Vydalo
1993
Stránok
186
EAN
9783540567134
ISBN
3540567135
Enbook ID
05274308
Hmotnosť
640
Rozmery
216 x 279 x 10

Kompletný popis

Given a familiar object extracted from its surroundings, we§humans have little difficulty in recognizing it irrespective§of its size, position and orientation in our field of view.§Changes in lighting and the effects of perspective also pose§no problems. How do we achieve this, and more importantly,§how can we get a computer to do this? One very promising§approach is to find mathematical functions of an object's§image, or of an object's 3D description, that are invariant§to the transformations caused by the object's motion.§This book is devoted to the theory and practice of such§invariant image features, so-called image invariants, forplanar objects. It gives a comprehensive summary of the§field, discussing methods for recognizing both occluded and§partially occluded objects, and also contains a definitive§treatmentof moment invariants and a tutorial introduction§to algebraic invariants, which are fundamental to affine§moment invariants and to many projective invariants.§A number of novel invariant functions are presented and the§results of numerous experiments investigating the stability§of new and old invariants are discussed. The main conclusion§is that moment invariants are very effective, both for§partially occluded objects and for recognizing objects in§grey-level images.

Mohlo by vás zaujímať

27.34
14.30
9.50

Dutch House

Patchett
10.09
15.18
5.38

Bluey: Copycat

PENGUIN YOUNG READERS
4.99

Here One Moment

Liane Moriarty
8.22

Zákazníci, ktorí si kúpili túto knihu, kúpili tiež

42.14
46.65
17.34
6.04
8.71
7.93