Feature-based texture classification of side-scan sonar images using a neural network approach

Research output: Contribution to journalArticle

Abstract

A texture classification system for side-scan sonar images by using a trained multilayer feedforward neural network (MFNN) is presented. The system classified textures by exploiting principal feature patterns, giving a high correct-classification rate. Experimental examples for the classification of side-scan sonar images are provided.

Original languageEnglish
Pages (from-to)2165-2167
Number of pages3
JournalElectronics Letters
Volume28
Issue number23
Publication statusPublished - 5 Nov 1992

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