Abstract
This paper discusses a pattern recognition problem of Multi-type Objects from a scene or video. A visual recognition system is developed to realize recognition and search of Multi-type Objects. The recognition approach combined with Genetic Algorithms (GA) and Neural Network (NN) is proposed. Using Neural Network, Color Statistical Models (CSM) are learned to classify multi-type objects by representing the feature of Multi-type Objects. GA is applied to search objects in the scene and to obtain the position and classification attribute of objects by embedded NN recognition. Accordingly, using GA and embedded NN, we can realize search and recognition of multi-type objects from the scenes or animated scenes of nature. Moreover, the applications of visual recognition for a Harvesting Robot are carried out and the validity of approach is verified.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
