DocumentCode :
2867689
Title :
Aircraft recognition from satellite images
Author :
Oturak, Mehmet ; Yuksel, Seniha Esen
Author_Institution :
Uzay Teknolojileri Arastirma Enstitusu, TUBITAK UZAY, Ankara, Turkey
fYear :
2015
fDate :
16-19 May 2015
Firstpage :
719
Lastpage :
722
Abstract :
In this work, rapid and high-accurate aircraft detection method in satellite images is developed. To this end, AdaBoost learning algorithm is used and Viola-Jones´ near real time and high-accurate face detector utilizing haar-like features is taken as reference. In existing studies, for a sub window to be positive, it must pass through all the strong classifiers as positive. However, in this work the strong classifier output values are summed up and compared to a threshold value as well. Therefore, besides the cascade structure´s ability to eliminate negative sub windows rapidly, more elaborate evaluation is made on the class of sub window, giving rise to a high performance classifier.
Keywords :
face recognition; image classification; image recognition; learning (artificial intelligence); object detection; remote sensing; AdaBoost learning algorithm; Viola-Jones near real time; aircraft detection method; aircraft recognition; cascade structure ability; classifier output values; haar-like features; high-accurate face detector; high-performance classifier; negative subwindow elimination; satellite images; threshold value; Aircraft; Boosting; Feature extraction; Image recognition; Real-time systems; Satellites; Support vector machines; AdaBoost; Aircraft Recognition; Classifier; Haar-like features;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
Type :
conf
DOI :
10.1109/SIU.2015.7129927
Filename :
7129927
Link To Document :
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