Title :
Comparing several AFE tools in the context of ships and vehicles detection based on RGB and EO data
Author :
Leduc, François ; Lavigne, Daniel A.
Author_Institution :
DRDC Valcartier, Quebec
Abstract :
In this paper we present a comparison of three AFE tools used in the context of ship and vehicle detection based on high resolution data. The three tools (Genie Pro - Los Alamos National Laboratory, Feature Analyst - Visual Learning Systems and eCognition - Definiens AG) were chosen because they were defined as promising and were to be analyzed by NGA in the framework of the STAR program. The comparison is presented here in terms of detection and false alarm rates and also in terms of pros and cons of each tool.
Keywords :
evolutionary computation; feature extraction; learning (artificial intelligence); object-oriented methods; ships; vehicles; AFE tools; EO data; Feature Analyst; Genie Pro; RGB; STAR program; assisted feature extraction; eCognition; high resolution data; ships; vehicle detection; Data mining; Feature extraction; Image analysis; Laboratories; Learning systems; Marine vehicles; Pixel; Shape; Surveillance; Vehicle detection; AFE; ATD/ATR; Definiens; Feature Analyst; Genie Pro; eCognition; target detection;
Conference_Titel :
Information Fusion, 2007 10th International Conference on
Conference_Location :
Quebec, Que.
Print_ISBN :
978-0-662-45804-3
Electronic_ISBN :
978-0-662-45804-3
DOI :
10.1109/ICIF.2007.4407991
