Video Based Object Recognition by Gokus Ahmet (7 results)

Paperback. Condition: Brand New. 68 pages. 8.66x5.91x0.16 inches. In Stock.

Taschenbuch. Condition: Neu. Video based Object Recognition for Conveyor Line Automation | Object Recognition | Ahmet Emre Gokus (u. a.) | Taschenbuch | 68 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846592458 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The aim of this book is to introduce a vision based object recognition system for automation of assembly line. The vision system is designed to recognize the objects, which are placed on the assembly line and also to identify the exact position for tracking each particular object, in order to lead the robot manipulator system for further processing. The method consists of an object shape discrimination analysis methodology using image processing techniques for the video frames acquired through the CCD camera over the conveyor line. The recognition of objects have been tested and evaluated using three different feature extraction methods on twenty objects for model conveyer line. These methods utilize geometric features, two dimensional moments and one dimensional scaled normalizing moments. The one dimensional scaled normalized moment method has been reported to be the best one for the object recognition. The neural network classifier is constructed for the features using the theoretical principles of artificial neural networks (ANN). Furthermore a step-by-step methodology for designing a neural network structure for the proposed system has been introduced. 68 pp. Englisch.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The aim of this book is to introduce a vision based object recognition system for automation of assembly line. The vision system is designed to recognize the objects, which are placed on the assembly line and also to identify the exact position for tracking each particular object, in order to lead the robot manipulator system for further processing. The method consists of an object shape discrimination analysis methodology using image processing techniques for the video frames acquired through the CCD camera over the conveyor line. The recognition of objects have been tested and evaluated using three different feature extraction methods on twenty objects for model conveyer line. These methods utilize geometric features, two dimensional moments and one dimensional scaled normalizing moments. The one dimensional scaled normalized moment method has been reported to be the best one for the object recognition. The neural network classifier is constructed for the features using the theoretical principles of artificial neural networks (ANN). Furthermore a step-by-step methodology for designing a neural network structure for the proposed system has been introduced.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gokus Ahmet EmreAhmet Emre Gokus received his MSc Degree from the Department of Electrical and Electronic Engineering, Eastern Mediterranean University in 2008. Assoc. Prof. Dr. Hasan Demirel received his PhD degree from Imperial Col. …

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The aim of this book is to introduce a vision based object recognition system for automation of assembly line. The vision system is designed to recognize the objects, which are placed on the assembly line and also to identify the exact position for tracking each particular object, in order to lead the robot manipulator system for further processing. The method consists of an object shape discrimination analysis methodology using image processing techniques for the video frames acquired through the CCD camera over the conveyor line. The recognition of objects have been tested and evaluated using three different feature extraction methods on twenty objects for model conveyer line. These methods utilize geometric features, two dimensional moments and one dimensional scaled normalizing moments. The one dimensional scaled normalized moment method has been reported to be the best one for the object recognition. The neural network classifier is constructed for the features using the theoretical principles of artificial neural networks (ANN). Furthermore a step-by-step methodology for designing a neural network structure for the proposed system has been introduced.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.…