Abstract
This paper presents an approach for the recognition of similar objects automatically. In the recognition system, colour features were extracted from two dimensional (2-D) pose images of every 3-D object given and the classification of the objects was realized by using these feature vectors in General Regression Neural Networks-GRNN. The system has been simulated with eight different objects having similar shapes and high recognition rate was obtained. The ability of recognizing many undefined objects after training with low number of samples is important property of this system.
Keywords
Artificial intelligence
Computer science
Pattern recognition (psychology)
Property (philosophy)
Cognitive neuroscience of visual object recognition
Feature extraction
Object (grammar)
Feature (linguistics)
Artificial neural network
Computer vision
Subject Areas
Neural Networks and Applications
·Artificial Intelligence ·Physical Sciences
Image and Video Stabilization
·Computer Vision and Pattern Recognition ·Physical Sciences
Image Retrieval and Classification Techniques
·Computer Vision and Pattern Recognition ·Physical Sciences
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