Infrared Ship Multi-Targets Recognizing

Author

Jun-Wei, Lu ; Jian-Cun, Ren ; Ting, Wang ; Chen-Gang, Wang ; Xiao-Hu, Yuan

Author_Institution

Dept. of Control Eng., Naval Aeronaut. Eng. Inst., Yantai

Volume

1

fYear

2006

fDate

4-6 Oct. 2006

Firstpage

418

Lastpage

423

Abstract

The technique of ship multi-targets recognizing is very important to anti-warship missile imaging guidance. In this paper, an algorithm is suggested to distinguish a ship target from the other ones in infrared images. The segmentation images by thresholds and by a mask of L inverted is used to draw ship targets out of infrared image. The rates of frontier in each region and gray-level classes are also utilized to merge regions. Four features are defined to describe infrared ship targets. A criterion based on BP neural network with these four features is set up to distinguish one ship target from the other ones. A complete algorithm is presented. This algorithm was tested in simulating platform with twenty-five images. The results showed this algorithm is valid when the side of the ship faces the camera. The further studies are needed to do for more situations

Keywords

backpropagation; image segmentation; infrared imaging; military equipment; neural nets; radar target recognition; ships; BP neural network; antiwarship missile imaging guidance; image masking; image segmentation; images thresholding; infrared image; infrared ship multitargets recognition; Engines; Image recognition; Image segmentation; Infrared imaging; Marine vehicles; Missiles; Neural networks; Ocean temperature; Systems engineering and theory; Testing; image guidance; image segmentation; infrared ship target; multi-targets recognizing; ship feature;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Engineering in Systems Applications, IMACS Multiconference on

Conference_Location

Beijing

Print_ISBN

7-302-13922-9

Electronic_ISBN

7-900718-14-1

Type

conf

DOI

10.1109/CESA.2006.4281689

Filename

4281689