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Titlebook: Segmentation and Separation of Overlapped Latent Fingerprints; Algorithms, Techniqu Branka Stojanović,Oge Marques,Aleksandar Nešković Book

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Latent Fingerprint Matching Systems,nt fingerprints. It introduces the matching process itself, including classical manual latent fingerprints matching procedures. It also presents the design of a modern automated latent fingerprints matching system and describes its main components and steps.
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Latent Fingerprint Datasets,s special attention to the Vlatacom dataset, created by the authors and publicly available, which consists of 120,000 synthetically overlapped test images (and the associated masks), with and without noise, processed with three different rotation angles, and in two variations of overall brightness.
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Machine Learning Based Segmentation of Overlapped Latent Fingerprints, block within the overlapped fingerprint image into three classes—background (B), single fingerprint (S), and overlapped fingerprint (O). The proposed segmentation method has been successfully tested on three different datasets.
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Machine Learning Based Separation of Overlapped Latent Fingerprints,ientation fields, which are then post-processed to correct remaining errors and enhanced using the global orientation field enhancement model. The proposed separation method has been successfully tested on two different datasets.
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Latent Fingerprint Datasets,s special attention to the Vlatacom dataset, created by the authors and publicly available, which consists of 120,000 synthetically overlapped test images (and the associated masks), with and without noise, processed with three different rotation angles, and in two variations of overall brightness.
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