Bastan, MuhammetByeon, WonminBreuel, Thomas M.2025-10-242025-10-242013#DEĞER!https://doi.org/10.5244/C.27.130https://hdl.handle.net/20.500.12899/399824th British Machine Vision Conference -- SEP 09-13, 2013 -- Bristol, ENGLANDObject 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.eninfo:eu-repo/semantics/openAccess[No Keywords]Conference Object10.5244/C.27.130WOS:000346352700127N/A