Roof Detection on Satellite Images
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In digital image classification processes, image pixels are separated according to some features that they have. Satellite images are digital images that are taken by a satellite vehicle through some sensors which perceive the specific wavelength of the light. In this study, two different digital image classification method (Linear Discriminant Analysis and Normalized Distance Values) have compared to each other, using different color spaces (RGB, L*a*b* and HSV), on the satellite images that have been taken by digital airborne sensors so as to detect roof objects. The common features of the applied methods are those they are supervised because of using training data given previously and they run fast because of operating linearly using a threshold value. For this reason, some of the images in the dataset are used for the purpose of training in order to detect the certain coefficients and the threshold value. The dataset we used for training and testing are the images acquired from ISPRS WG III/4 2D Semantic Labeling database. In the database, the classification ground truth images are also available.
Açıklama
25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY
Anahtar Kelimeler
satellite images, classification, linear discriminant analysis, normalized distance values
Kaynak
2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
