Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Kurt saldırıları için sentetik irislerde örnek seçilimi(IEEE, 2023) Akdeniz, Eyüp Kaan; Erdoğmuş, NesliIn this study, samples with higher potential to succeed in wolf attacks are picked among synthetically generated iris images, and the composed subset is shown to pose a more significant threat toward an iris recognition system backed by a Presentation Attack Detection (PAD) module with respect to randomly selected samples. Iris images generated by Deep Convolutional Generative Adversarial Networks (DCGAN) are firstly filtered by rejection sampling on PAD score distribution of real iris image PAD scores. Next, the probability of zero success in all attack attempts is calculated for each synthetic iris image, using real iris images in the training set, and match and non-match score distributions are calculated on those. Synthetic images with the lowest probabilities of zero success are included in the final set. Our hypothesis that this set would be more successful in wolf attacks is tested by comparing its spoofing performances with randomly selected sample sets.Conference Object Citation - WoS: 1Citation - Scopus: 2Scene text localization using keypoints(Institute of Electrical and Electronics Engineers Inc., 2015) Erdoğmuş, Nesli; Özuysal, MustafaScene text localization and recognition (also known as text localization and recognition in real-world images, nature scene OCR or text-in-the-wild problem) is an open problem, attracting increasing interest from researchers. In this paper, we address the localization issue and leave the recognition part out of its scope. For the purpose of scene text localization, Scale-Invariant Feature Transform (SIFT) keypoints are extracted from the images and classified as text and non-text. Subsequently, the text keypoints are utilized to compute the bounding boxes around text regions. The proposed technique is tested on the database of ICDAR 2013 Robust Reading Competition-Challenge 2 and the experimental results are reported in detail. Although the idea introduced here is still at its infancy, it is observed to achieve remarkable results and due to the fact that there is a large room for improvement, it is found to be promising.