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Automatic target detection of sonar images using multi-modal threshold and connected component theory

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Title Automatic target detection of sonar images using multi-modal threshold and connected component theory
 
Creator Das, Subhra Kanti
Banerjee, Soma
Pal, Dibyendu
Nandy, Sambhunath
Shome, Sankar Nath
Mukherjee, Somnath
 
Subject SONAR
Automatic target detection
Thresholding
Features-detection
Acoustic image
 
Description 267-279
The aim of this paper is to present a complete progressive development of
object detection from underwater acoustic images. Object detection with respect
to automatic target detection in underwater autonomous vehicle system is still
in a severe problem in context of surveillance and other defense activity. The
present work is based on robust method in perspective of segmentation and
feature extraction. Underwater acoustic images suffer from typical noise
associations and are often of low contrast. In this perspective, a multi-modal
thresholding is adopted for automatic segmentation of the images thus obtained
and a graph theoretic approach based on connected components is formulated in
order to interpret features embedded within the image context. An imaging SONAR
is used for carrying out necessary experimental work. The proposed algorithm is
executed in comparison with multi-level thresholding and K-means
clustering. Effectiveness is established in the context of both running time
and quality of processed image as well. The latter aspect is determined by a
Figure of Merit (FOM) parameter.
 
Date 2016-07-04T09:41:46Z
2016-07-04T09:41:46Z
2015-02
 
Type Article
 
Identifier 0975-1033 (Online); 0379-5136 (Print)
http://hdl.handle.net/123456789/34647
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJMS Vol.44(02) [February 2015]