Object Recognition Based on Modified Invariant Moments

被引：5

作者：

Zhang, Lei ^{[1
]}

Pu, Jiexin ^{[1
]}

Yu, Jia ^{[1
]}

机构：

[1] Henan Univ Sci & Technol, Coll Elect & Informat Engn, Luoyang, Henan Province, Peoples R China

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS 1-7, CONFERENCE PROCEEDINGS | 2009年

关键词：

objects recognition; feature extraction; invariant moments; norm;

D O I：

10.1109/ICISE.2009.263

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a novel method for object recognition in noise free and noisy environments, based on modified invariant moments and minimum norm. First, the modified invariant moments of different objects are extracted by using invariant moments. Then the norms of feature vectors are computed by using norm theory of functional analysis. Finally, classification and recognition object are accomplished according to the computed results, furthermore, objects do not need to be trained in the paper. The algorithm is simple and the recognition rate is rather high. Moreover, the objects with noise are able to be recognized correctly. Experimental results demonstrate that the proposed algorithm is invariant to the translation, rotating and scaling of objects. So the efficiency is proved in the paper.

引用

页码：2542 / 2547

页数：6

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