Recognition of 3-D Similar Objects by GRNN

O. Polat, T. Yıldırım
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引用次数: 1

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
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基于GRNN的三维相似物体识别
本文提出了一种自动识别相似物体的方法。在识别系统中,从给定的每个三维物体的二维(2-D)姿态图像中提取颜色特征,并利用这些特征向量在广义回归神经网络- grnn中实现物体的分类。对8个形状相近的物体进行了仿真,获得了较高的识别率。经过少量样本训练后,识别大量未定义对象的能力是该系统的重要特性
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