Object Recognition in Multi-View Dual Energy X-ray Images
Küçük Resim Yok
Tarih
2013
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
B M V A Press
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Object recognition in X-ray images is an interesting application of machine vision that can help reduce the workload of human operators of X-ray scanners at security checkpoints. In this paper, we first present a comprehensive evaluation of image classification and object detection in X-ray images using standard local features in a BoW framework with (structural) SVMs. Then, we extend the features to utilize the extra information available in dual energy X-ray images. Finally, we propose a multi-view branch-and-bound algorithm for multi-view object detection. Through extensive experiments on three object categories, we show that the classification and detection performance substantially improves with the extended features and multiple views.
Açıklama
24th British Machine Vision Conference -- SEP 09-13, 2013 -- Bristol, ENGLAND
Anahtar Kelimeler
[No Keywords]
Kaynak
Proceedings Of The British Machine Vision Conference 2013
WoS Q Değeri
N/A
