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dc.contributor.authorKusban, Muhammad
dc.date.accessioned2016-10-21T09:22:48Z
dc.date.available2016-10-21T09:22:48Z
dc.date.issued2016-08-27
dc.identifier.citation[1] Junta Doi and Masaaki Yamanaka, ”Discrete Finger and Palmar Feature Extraction for Personal Authentication”, IEEE Transact., Vol. 54, pp. 2213- 2219, 2005. [2] Yingbo Zhou and Ajay Kumar, ”Human Identification Using Palm-Vein Images”, IEEE Transactions, vol. 6, pp. 1259-1274, 2011. [3] Wenxiong Kang and Qiuxia Wu, ”Contactless palm vein recognition using a mutual foreground-based local binary pattern”, IEEE Transactions, vol. 9, pp. 1974-1985, 2014. [4] Wei Jia, et al., ”Histogram of Oriented Lines for Palmprint Recognition”, Ieee Transactions, vol. 44, pp. 385-395, 2014. [5] David Zhang, et al., ”An Online System of Multispectral Palmprint Verification”, IEEE Transactions, vol. 59, pp. 480-490, 2010. [6] J. Lu, et al., ”Enhanced Gabor-based region covariance matrices for palmprint recognition”, Electronics Letters, vol. 45, pp. 880, 2009. [7] Feng Yue, et al., ”Hashing Based Fast Palmprint Identification for Large-Scale Databases”, IEEE Transactions, vol. 8, pp. 769-778, 2013. [8] Raffaele Cappelli, et al., ”A fast and accurate palmprint recognition system based on minutiae”, IEEE transactions, vol. 42, pp. 956-962, 2012. [9] Zhenhua Guo, ”Feature Band Selection for Online Multispectral Palmprint Recognition”, IEEE Transactions, vol. 7, pp. 1094-1099, 2012. [10] R Raghavendra and Christoph Busch, ”Novel image fusion scheme based on dependency measure for robust multispectral palmprint recognition”, Pattern Recognition, vol. 47, pp. 2205-2221, 2014. [11] Jeen-Shing Wang, et al., ”A k-nearest-neighbor classifier with heart rate variability feature- based transformation algorithm for driving stress recognition”, Neurocomputing, vol.116, pp. 136-143, 2013. [12] Moussadek Laadjel, et al., ”Combining Fisher locality preserving projections and passband DCT for efficient palmprint recognition”, Neurocomputing, vol. 152, pp. 179-189, 2015. [13] LinLin Shen, et at., ”Gabor wavelets and general discriminant analysis for face identification and verification”, ScienceDirect - Image and Vision Computing, vol.25, pp. 553-563, 2007. [14] LinLin Shen, et at., ”Gabor wavelets and general discriminant analysis for face identification and verification”, ScienceDirect - Image and Vision Computing, vol.25, pp. 553-563, 2007. [15] Jifeng Dai, et al., ”Robust and Efficient Ridge-Based Palmprint Matching”, IEEE Transactions, vol. 34, pp. 1618-1632, 2012. [16] Lu´ cia Carreira, et al., ”Personal identification from degraded and incomplete high resolution palmprints”, IET Biometrics, vol. 4, pp. 53-61,205. [17] J. Dai and J. Zhou, ”Multifeature-Based High- Resolution Palmprint Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, pp. 945-957, 2011. [18] C. Lakshmi Deepika and A. Kandaswamy and C. Vimal and B. Satish, ”Palmprint authentication using modified legendre moments”, Procedia Computer Science, vol. 2, pp. 164 - 172, 2010. [19] Michael, Goh Kah Ong and Connie, Tee and Teoh, Andrew Beng Jin, ”A Contactless Biometric System Using Multiple Hand Features”, J. Vis. Comun. Image Represent., vol. 23, pp. 1068-1084, 2010.in_ID
dc.identifier.issn2407-9189
dc.identifier.urihttp://hdl.handle.net/11617/7744
dc.description.abstractStraightforward to improve performance of the palmprint recognition is using appropriate filter. Skeleton filter, a system in image processing is tool to seek objects within a defined scope area for further altering into line object 1 pixel lengthwise. When combined with the 8 × 5 orientation and scale of the Gabor method and reduced by the dimension reduction of KernelPCA-based will enhance performance of the verification system. From the research that have been done, using the algorithms was successfully obtained the EER rate approximately 0, 00188 and verification about 99, 818%.in_ID
dc.language.isoidin_ID
dc.publisherSTIKES Muhammadiyah Pekajanganin_ID
dc.subjectPalmprint recognitionin_ID
dc.subjectskeleton filterin_ID
dc.subjectscale orientation Gabor methodin_ID
dc.subjectKPCAin_ID
dc.subjectEERin_ID
dc.titlePerbaikan Proses Identifikasi Sidik Jari Dengan Metode Skeleton Image Enhancementin_ID
dc.typeArticlein_ID


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