NDLI: Automatic target detection by optimal morphological filters

Content Provider	Springer Nature Link
Author	Yu, ng Wu, Hao Wu, ChangYong Li, YuShu
Copyright Year	2003
Abstract	It is widely accepted that the design of morphological filters, which are optimal in some sense, is a difficult task. In this paper a novel method for optimal learning of morphological filtering parameters (Genetic training algorithm for morphological filters, GTAMF) is presented. GTAMF adopts new crossover and mutation operators called the curved cylinder crossover and master-slave mutation to achieve optimal filtering parameters in a global searching. Experimental results show that this method is practical, easy to extend, and markedly improves the performances of morphological filters. The operation of a morphological filter can be divided into two basic problems including morphological operation and structuring element (SE) selection. The rules for morphological operations are predefined so that the filter's properties depend merely on the selection of SE. By means of adaptive optimization training, structuring elements possess the shape and structural characteristics of image targets, and give specific information to SE. Morphological filters formed in this way become certainly intelligent and can provide good filtering results and robust adaptability to image targets with clutter background.
Starting Page	29
Ending Page	40
Page Count	12
File Format	PDF
ISSN	10009000
Journal	Journal of Computer Science and Technology
Volume Number	18
Issue Number	1
e-ISSN	18604749
Language	English
Publisher	Science Press
Publisher Date	2003-01-01
Publisher Place	Beijing
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	image analysis morphological filter genetic algorithm optimizing calculation Computer Science Software Engineering Theory of Computation Data Structures, Cryptology and Information Theory Artificial Intelligence (incl. Robotics) Information Systems Applications (incl.Internet)
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computational Theory and Mathematics Computer Science Applications Software Hardware and Architecture

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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