Robust real-time mine classification based on side-scan sonar imagery

Martin G. Bello

doi:10.1117/12.396265

22 August 2000 Robust real-time mine classification based on side-scan sonar imagery

Martin G. Bello

Proceedings Volume 4038, Detection and Remediation Technologies for Mines and Minelike Targets V; (2000) https://doi.org/10.1117/12.396265
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

We describe here image processing and neural network based algorithms for detection and classification of mines in side-scan sonar imagery, and the results obtained from their application to two distinct image data bases. These algorithms evolved over a period from 1994 to the present, originally at Draper Laboratory, and currently at Alphatech Inc. The mine-detection/classification system is partitioned into an anomaly screening stage followed by a classification stage involving the calculation of features on blobs, and their input into a multilayer perceptron neural network. Particular attention is given to the selection of algorithm parameters, and training data, in order to optimize performance over the aggregate data set.

Citation Download Citation

Martin G. Bello "Robust real-time mine classification based on side-scan sonar imagery", Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); https://doi.org/10.1117/12.396265

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available