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Sökning: WFRF:(Awad Ali Ismail)

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  • Awad, Ali Ismail, et al. (författare)
  • Bag-of-Visual-Words for Cattle Identification from Muzzle Print Images
  • 2019
  • Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 9:22
  • Tidskriftsartikel (refereegranskat)abstract
    • Cattle, buffalo and cow identification plays an influential role in cattle traceability from birth to slaughter, understanding disease trajectories and large-scale cattle ownership management. Muzzle print images are considered discriminating cattle biometric identifiers for biometric-based cattle identification and traceability. This paper presents an exploration of the performance of the bag-of-visual-words (BoVW) approach in cattle identification using local invariant features extracted from a database of muzzle print images. Two local invariant feature detectors—namely, speeded-up robust features (SURF) and maximally stable extremal regions (MSER)—are used as feature extraction engines in the BoVW model. The performance evaluation criteria include several factors, namely, the identification accuracy, processing time and the number of features. The experimental work measures the performance of the BoVW model under a variable number of input muzzle print images in the training, validation, and testing phases. The identification accuracy values when utilizing the SURF feature detector and descriptor were 75%, 83%, 91%, and 93% for when 30%, 45%, 60%, and 75% of the database was used in the training phase, respectively. However, using MSER as a points-of-interest detector combined with the SURF descriptor achieved accuracies of 52%, 60%, 67%, and 67%, respectively, when applying the same training sizes. The research findings have proven the feasibility of deploying the BoVW paradigm in cattle identification using local invariant features extracted from muzzle print images. 
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  • Awad, Ali Ismail (författare)
  • Fast Fingerprint Orientation Field Estimation Incorporating General Purpose GPU
  • 2016
  • Ingår i: Soft Computing Applications. - New York : Encyclopedia of Global Archaeology/Springer Verlag. - 9783319184159 - 9783319184166 ; , s. 891-902
  • Konferensbidrag (refereegranskat)abstract
    • Fingerprint is one of the broadly utilized biometric traits for personal identification in both civilian and forensic applications due to its high acceptability, strong security, and low cost. Fingerprint ridge orientation is one of the global fingerprint representations that keeps the holistic ridge structure in a small storage area. The importance of fingerprint ridge orientation comes from its usage in fingerprint singular point detection, coarse level classification, and fingerprint alignment. However, processing time is an important factor in any automatic fingerprint identification system, estimating that ridge orientation image may consume long processing time. This research presents an efficient ridge orientation estimation approach by incorporating a Graphics Processing Unit (GPU) capability to the traditional pixel gradient method. The simulation work shows a significant enhancement in ridge orientation estimation time by 6.41x using a general purpose GPU in comparison to the CPU execution.
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