Advances in Object Recognition Systems

An invariant object recognition system needs to be able to recognise the object under any usual a priori defined distortions such as translation, scaling and in-plane and out-of-plane rotation. Ideally, the system should be able to recognise (detect and classify) any complex scene of objects even wi...

Full description

Saved in:
Bibliographic Details
Other Authors: Kypraios, Ioannis (Editor)
Format: Book Chapter
Published: IntechOpen 2012
Subjects:
Online Access:Get Fullteks
DOAB: description of the publication
Tags: Add Tag
No Tags, Be the first to tag this record!
LEADER 02551naaaa2200289uu 4500
001 doab_20_500_12854_66073
005 20210420
020 |a 2392 
020 |a 9789535105985 
020 |a 9789535156468 
024 7 |a 10.5772/2392  |c doi 
041 0 |a English 
042 |a dc 
072 7 |a UYQV  |2 bicssc 
100 1 |a Kypraios, Ioannis  |4 edt 
700 1 |a Kypraios, Ioannis  |4 oth 
245 1 0 |a Advances in Object Recognition Systems 
260 |b IntechOpen  |c 2012 
300 |a 1 electronic resource (184 p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a An invariant object recognition system needs to be able to recognise the object under any usual a priori defined distortions such as translation, scaling and in-plane and out-of-plane rotation. Ideally, the system should be able to recognise (detect and classify) any complex scene of objects even within background clutter noise. In this book, we present recent advances towards achieving fully-robust object recognition. The relation and importance of object recognition in the cognitive processes of humans and animals is described as well as how human- and animal-like cognitive processes can be used for the design of biologically-inspired object recognition systems. Colour processing is discussed in the development of fully-robust object recognition systems. Examples of two main categories of object recognition systems, the optical correlators and pure artificial neural network architectures, are given. Finally, two examples of object recognition's applications are described in details. With the recent technological advancements object recognition becomes widely popular with existing applications in medicine for the study of human learning and memory, space science and remote sensing for image analysis, mobile computing and augmented reality, semiconductors industry, robotics and autonomous mobile navigation, public safety and urban management solutions and many more others. This book is a "must-read" for everyone with a core or wider interest in this "hot" area of cutting-edge research. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by/3.0/  |2 cc  |4 https://creativecommons.org/licenses/by/3.0/ 
546 |a English 
650 7 |a Computer vision  |2 bicssc 
653 |a Image processing 
856 4 0 |a www.oapen.org  |u https://mts.intechopen.com/storage/books/1976/authors_book/authors_book.pdf  |7 0  |z Get Fullteks 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/66073  |7 0  |z DOAB: description of the publication