Emrah Basaran

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In this paper, it is shown that Local Zernike Moments (LZM), applied successfully to face recognition, can also be used successfully for the classification of traffic signs. The direct usage of the images produced by LZM is not very efficient in terms of computation time. So, a new method, named Quantized Local Zernike Moments (QLZM), is developed. QLZM has(More)
In this paper, a new method that extracts the features from the complex Local Zernike Moments (LZM) images around facial landmarks is proposed. In this method, multiple grids which are in different sizes are located on landmarks and Phase-Magnitude (PM) histograms are calculated in each cells of these grids. The PM histograms are calculated for every(More)
In this paper, an efficient face recognition scheme using Local Zernike Moments (LZM) is introduced. LZM is a localized version of Zernike Moments used successfully for character and fingerprint recognition. The superiority of LZM over LBP and Gabor methods on FERET dataset has been shown in previous studies. In this study, we demonstrate that Block Based(More)
In recent years, identification systems with using biometric features are receiving considerable attention. Iris, palmprint, fingerprint and footprint are shown as examples. This paper focused on footprint identification without features extraction. CASIA Database, Dataset-D used for identification database. Dataset-D contain footprint images taken from(More)
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