Hybrid Pattern Recognition System for Detecting Buried Object in GPR Images
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
BIOAXIS DNA RESEARCH CENTRE PRIVATE LIMITED
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
It is very difficult to evaluate the shape of the buried objects using Ground Penetrating Radar (GPR). In this study, 180 GPR B scan images were classified by using different classification algorithms. GPR-B scan images of objects with different shapes in various depths were obtained by using GprMax simulation program. Noise in these images were eliminated by Wavelet transform and then, Gray Level Co-occurrence Matrices (GLCM), run length matrix (RLM) and Autocorrelation function (ACF) features were extracted from the segmented images Some feature reduction methods, which are Principle Component Analysis and Independent Component Analysis, provided that size of the feature vectors was decreased. All the modified vectors were given as inputs to various classifiers. Outputs of the classifier systems were evaluated and compared with each other. Accuracy values of proposed algorithm results were computed. Consequently, it is possible to use in real application of GPR devices.
Açıklama
Anahtar Kelimeler
Kaynak
HELIX
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
8
Sayı
2
