A model-based Sonar image ATR method based on SIFT features

Author

Zhaotong Zhu ; Xiaomei Xu ; Liangliang Yang ; Huicheng Yan ; Shibao Peng ; Jia Xu

Author_Institution

Key Lab. of Underwater Acoust. Commun., Xiamen Univ., Xiamen, China

fYear

2014

fDate

7-10 April 2014

Firstpage

1

Lastpage

4

Abstract

Sonar image automatic target recognition (ATR) is urgently needed in large-scale marine investigation. A modelbased Sonar image ATR method based on SIFT features is proposed in this paper. The proposed method can realize ATR for arbitrary shaped target by physically model 3D under water scene, generate simulated template images, extract Scale-invariant feature transform (SIFT) keypoints and matching target image and template image. Simulation result shows, the proposed method can reach relatively high probability of correct classification with small size of template library.

Keywords

feature extraction; image classification; image matching; oceanographic techniques; probability; radar imaging; sonar imaging; transforms; SIFT features; correct classification probability; large-scale marine investigation; model-based sonar image ATR method; physical model 3D under water scene; scale-invariant feature transform keypoint extraction; simulated template image generation; sonar image automatic target recognition; target image matching; template image matching; template library; Feature extraction; Libraries; Simulation; Solid modeling; Synthetic aperture sonar; Three-dimensional displays; ATR; SAS; SIFT; Sonar image;

fLanguage

English

Publisher

ieee

Conference_Titel

OCEANS 2014 - TAIPEI

Conference_Location

Taipei

Print_ISBN

978-1-4799-3645-8

Type

conf

DOI

10.1109/OCEANS-TAIPEI.2014.6964476

Filename

6964476