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Proceedings Paper

Warship detection in smoke screen interference based on region of interest for CMAC-prediction
Author(s): Xiaoke Yan; Caicheng Shi
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Paper Abstract

Warship detection in smoke screen interference background belongs to the field of object extraction from image with low contrast and low signal/noise ratio. Aimed at the specialty of the complex background, a novel algorithm of warship detection in smoke screen interference based on region of interest for CMAC-prediction is proposed in the article. The regions-of-interest (ROI) must be predicted in target tracking of IR image for increasing capture probability. CMAC estimator can effectually resolve conflict between operational counts and predicting precision. The local fractal dimension is used to differentiate the warship from the ROI. The experimental results show that CMAC can accurately estimate the ROI and a similar performance in a low-noise environment and superiority of the fractal operators in a high noise, the algorithms are effectively for smoke screen interference and are easy to be implemented by parallel processing hardware.

Paper Details

Date Published: 8 October 2015
PDF: 4 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96751G (8 October 2015); doi: 10.1117/12.2199397
Show Author Affiliations
Xiaoke Yan, People's Liberation Army (China)
Caicheng Shi, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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