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doctoral thesis
Sustav za otkrivanje ukopanih mina
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2001. urn:nbn:hr:168:422954
Antonić, Davor
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Control and Computer Engineering

Cite this document

Antonić, D. (2001). Sustav za otkrivanje ukopanih mina (Doctoral thesis). Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:422954

Antonić, Davor. "Sustav za otkrivanje ukopanih mina." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2001. https://urn.nsk.hr/urn:nbn:hr:168:422954

Antonić, Davor. "Sustav za otkrivanje ukopanih mina." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2001. https://urn.nsk.hr/urn:nbn:hr:168:422954

Antonić, D. (2001). 'Sustav za otkrivanje ukopanih mina', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 18 January 2021, https://urn.nsk.hr/urn:nbn:hr:168:422954

Antonić D. Sustav za otkrivanje ukopanih mina [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2001 [cited 2021 January 18] Available at: https://urn.nsk.hr/urn:nbn:hr:168:422954

D. Antonić, "Sustav za otkrivanje ukopanih mina", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2001. Available at: https://urn.nsk.hr/urn:nbn:hr:168:422954

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Metadata
TitleSustav za otkrivanje ukopanih mina
AuthorDavor Antonić
MentorMario Žagar (mentor)
Committee memberNikola Bogunović (član povjerenstva)
Committee memberMario Žagar (član povjerenstva)
Committee memberMilan Bajić (član povjerenstva)
Committee memberGabro Smiljanić (član povjerenstva)
Committee memberLjubo Marangunić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Control and Computer Engineering)
Zagreb
Defense date and country2001-10-19, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Process Computing
Universal decimal classification
(UDC)		004
GENERALLY
Computer science and technology. Computing. Data processing
Universal decimal classification
(UDC)		623
APPLIED SCIENCES. MEDICINE. TECHNOLOGY
Military engineering
Abstract
U ovoj disertaciji opisan je razvoj i implementacija postupaka obrade signala, izdvajanja značajki i klasifikacije te njihovo povezivanje u cjelovit sustav prilagođen potrebama otkrivanja ukopanih mina. Razvijen je postupak automatskog generiranja i redukcije skupa značajki iz spektara signala kao i novi postupci izdvajanja značajki temeljeni na heurističkom pretraživanju stabla i genetskim algoritmima, primjenjivi na široku klasu problema. Svi predloženi postupci provjereni su na stvarnim minama i ostalim objektima. Primjena na skup uzoraka snimljenih sonarom rezultirala je značajnim smanjenjem složenosti klasifikacijskog sustava. Postupci su također ispitani na skupu uzoraka mina i ostalih objekata dobivenih detektorom temeljenim na standardnoj pirotehničarskoj pipalici koji bilježi vibracije nastale dodirom ukopanog predmeta, razvijenog u sklopu ove disertacije. Ispitivanje je pokazalo da predloženi sustav detektora i pripadnog skupa postupaka omogućuje razlikovanje mine od ostalih ukopanih predmeta. Definirana je i odgovarajuća informacijska podrška koja omogućuje prihvat informacija stvorenih na razini detekcije pojedinih mina, uključivanje tih informacija u informacijski sustav humanitarnog razminiranja i ostvarivanje povratne veze koja će omogućiti učenje i kontinuirano poboljšavanje svojstava sustava detekcije. U okviru definiranog sustava također su predloženi postupci praćenja položaja detektora smještenog na daljinski upravljanoj ili autonomnoj robotskoj platformi.
Abstract (english)
This thesis describes development and implementation of algorithms for signal processing, feature extraction and classification, as well as their integration into the system for buried landmine detection. Procedure for automatic generation and reduction of the initial feature set directly from signal spectrums has been developed. Novel feature extraction algorithms based on heuristic tree search and genetic algorithms, which are applicable to the wide range of problems have been proposed. All the algorithms were tested on real mines and other objects. Application to the set of sonar samples resulted in significant reduction of classification system complexity. Algorithms were also tested on mines and other objects samples. Samples were acquired by developed detector, based on standard deminer's prodder which records vibrations produced by touching the buried object. Testing shows that proposed detection system and dedicated set of procedures make mines distinguishable from other buried objects. Appropriate information support has been defined, which makes possible managing information created at the level of individual mines detection. It allows incorporation of the information into the humanitarian demining information system and establishment of feedback which will make possible learning and continuous improvement of detection system features. Methods for position tracking of the detector attached to the remotely controlled or autonomous robotic platform are also described.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:422954
Study programmeTitle: Computer Science
Study programme type: university
Study level: postgraduate
Academic / professional title: Doktor znanosti (Doktor znanosti)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
RepositoryFER Repository
Created on2019-04-23 07:14:24

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