Mean and standard deviation as features for palmprint recognition based on gabor filters

作者：Mu Meiru^*; Ruan Qiuqi

来源：International Journal of Pattern Recognition and Artificial Intelligence, 2011, 25(4): 491-512.

DOI：10.1142/S0218001411008750

• Decomposition coefficient
• Discriminative features
• Feature vectors
• Fisher linear discriminant analysis
• Fisher linear discriminations
• Gabor filter
• Gabor function
• Gabor wavelet transforms
• Hong-kong
• Localization properties
• Log-normal distribution
• Logarithmic transformations
• mean and standard deviation
• Palmprint feature extraction
• Palmprint recognition
• Palmprints
• PolyU Palmprint Database
• Recognition performance
• Spatial and frequency domain
• Standard deviation
• Sub-bands

The two-dimensional (2D) Gabor function has been recognized as a very useful tool in feature extraction of image, due to its optimal localization properties in both spatial and frequency domain. This paper presents a novel palmprint feature extraction method based on the statistics of decomposition coefficients of the Gabor wavelet transform. It is experimentally found that the magnitude coefficients of the Gabor wavelet transform within each subband uniformly to approximate the Lognormal distribution. Based on this fact, we create the palmprint representation using two simple statistics (mean and standard deviation) as feature components after applying the logarithmic transformation of Gabor filtered magnitude coefficients for each subband with different orientations and scales. The optimum setting of the number of Gabor filters and orientation of each Gabor filter is experimentally determined. For palmprint recognition, the popularly used Fisher Linear Discriminant (FLD) analysis is further applied on the constructed feature vectors to extract discriminative features and reduce dimensionality. All experiments are both executed over the CCD-based HongKong PolyU Palmprint Database of 7752 images and the scanner-based BJTU-PalmprintDB (V1.0) of 3460 images. The results demonstrate the effectiveness of the proposed palmprint representation in achieving the improved recognition performance.

• 出版日期2011
• 单位北京交通大学