A study on detecting and classifying underwater mine like objects using image processing techniques

Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 10

Abstract

Detection and classification of underwater mines among natural formations and debris along the sea floor is a tedious task. In order to overcome such scenario an automated computer aided detection and classification system is required. Image processing techniques are used to improve the performance of mine hunting operations using sector-scan, side-scan, magnetometers, cameras, etc. This paper serve as a strategic review of the potential for image processing techniques to aid the detection and classification of underwater mines and mine-like objects in side scan sonar imagery. Five basic components of any Computer-Aided Detection and Classification (CAD/CAC) technique are considered namely image preprocessing, segmentation, feature extraction, computer aided detection and computer aided classification. In this paper more than thirty research papers of image processing techniques are clearly reviewed.

Authors and Affiliations

Dr. S. N. Geethalakshmi , Dr. P. Subashini , Mrs. P. Geetha

Keywords

Related Articles

A Novel Session Based Dual Image Encoding and Hiding Technique Using DWT and Spread Spectrum

This work proposes a DWT based Steganographic technique. Cover image is decomposed into four sub bands using DWT. Two Encoded secret images are embedded within the HL and HH sub bands respectively. During embedding secre...

A generic Framework for Landmine detection using statistical classifier based on IR images

Landmine detection with passive infrared images can depend quite heavily on the environmental conditions, and there are cross over periods when the thermal contrast is negligible and the mines may be undetectable. Conven...

Software Reliability Analyzer for improving Software Quality and Reliability

A software product is tested throughout testing stage of the software development life cycle to check whether the software meets the user’s necessities or not. For forecasting the reliability of the software, software re...

ACO Based Feature Subset Selection for Multiple k-Nearest Neighbor Classifiers

The k-nearest neighbor (k-NN) is one of the most popular algorithms used for classification in various fields of pattern recognition & data mining problems. In k-nearest neighbor classification, the result of a new i...

CCMP-AES Model with DSR routing protocol to secure Link layer and Network layer in Mobile Adhoc Networks

Mobile Adhoc network is a special kind of wireless networks. It is a collection of mobile nodes without having aid of stablished infrastructure. Mobile Adhoc network are vulnerable to attacks compared to wired networks...

Download PDF file
  • EP ID EP124488
  • DOI -
  • Views 134
  • Downloads 0

How To Cite

Dr. S. N. Geethalakshmi, Dr. P. Subashini, Mrs. P. Geetha (2011). A study on detecting and classifying underwater mine like objects using image processing techniques. International Journal on Computer Science and Engineering, 3(10), 3359-3366. https://europub.co.uk./articles/-A-124488