An automated palmprint recognition system

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A survey of palmprint recognition (2009, methodology): “In addition to applying PCA, LDA and ICA directly to palmprint images, researchers also employ wavelets, Gabor, discrete cosine transform (DCT) and kernels in their methods [8, 18, 39, 42, 89, 91].”
Palmprint verification based on robust line orientation code (2007, methodology): “Finally, a matching algorithm based on pixel-to-area comparison has been designed, which has better fault tolerant ability.”
Palmprint verification based on principal lines (2008, background): “…for palmprint verification/identification, which can be mainly divided into five categories: (1) texture based approaches [1] [4]; (2) appearance based approaches [5] [6] [7] [8]; (3) multiple features based approaches [9]; (4) orientation based approaches [10] [11]; and * Corresponding author.”
A review of biometric technology along with trends and prospects (2014, background): “Table 4: Summary of behavioral modalities: Modality Feature Set Recognition Techniques Datasets Voice Spectrum, Glottal pulse features, pitch, energy, duration, rhythm, temporal features, phones, idiolects, semantics, accent, pronunciation, LPCC [204], MFCC [205], VQ [206-208], HMM [209], GMM [210, ”