Title :
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
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;
Conference_Titel :
OCEANS 2014 - TAIPEI
Conference_Location :
Taipei
Print_ISBN :
978-1-4799-3645-8
DOI :
10.1109/OCEANS-TAIPEI.2014.6964476
