Object Recognition Algorithm of Sonar Image

Author

Tian, Xiaodong ; Zhou, Dechao ; Liu, Zhong

Author_Institution

Inst. of Electron. Eng., Naval Univ. of Eng., Wuhan

Volume

2

fYear

2006

fDate

16-20 Nov. 2006

Abstract

In the target detection and recognition of underwater sonar image, object recognition is one of key technologies. With analysis and calculation, three features which have good distinguish degree are chosen to construct feature vector for classification, clustering method, neural network and support vector machine were presented. Correct classification ratio can be above 95%. Simulation result indicates that features presented in this paper have characteristics such as precision and robustness, which reduce dependence of classifying result on classifier

Keywords

image classification; neural nets; object detection; object recognition; sonar; support vector machines; clustering method; feature vector; image classification; neural network; object recognition algorithm; support vector machine; target detection; underwater sonar image; Clustering algorithms; Clustering methods; Image recognition; Neural networks; Object detection; Object recognition; Sonar detection; Support vector machine classification; Support vector machines; Target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2006 8th International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9736-3

Electronic_ISBN

0-7803-9736-3

Type

conf

DOI

10.1109/ICOSP.2006.345726

Filename

4129018