Touchless palmprint recognition systems enable high-accuracy recognition of individuals through less-constrained and highly usable procedures that do not require the contact of the palm with a ...surface. To perform this recognition, methods based on local texture descriptors and convolutional neural networks (CNNs) are currently used to extract highly discriminative features while compensating for variations in scale, rotation, and illumination in biometric samples. In particular, the main advantage of CNN-based methods is their ability to adapt to biometric samples captured with heterogeneous devices. However, the current methods rely on either supervised training algorithms, which require class labels (e.g., the identities of the individuals) during the training phase, or filters pretrained on general-purpose databases, which may not be specifically suitable for palmprint data. To achieve a high-recognition accuracy with touchless palmprint samples captured using different devices while neither requiring class labels for training nor using pretrained filters, we introduce PalmNet, which is a novel CNN that uses a newly developed method to tune palmprint-specific filters through an unsupervised procedure based on Gabor responses and principal component analysis (PCA), not requiring class labels during training. PalmNet is a new method of applying Gabor filters in a CNN and is designed to extract highly discriminative palmprint-specific descriptors and to adapt to heterogeneous databases. We validated the innovative PalmNet on several palmprint databases captured using different touchless acquisition procedures and heterogeneous devices, and in all cases, a recognition accuracy greater than that of the current methods in this paper was obtained.
This paper describes the design of color filter arrays (CFAs) used in the consumer-grade digital camera, and analyses their influence on the performance of the demosaicking process. Of particular ...interest are RGB CFAs widely used in a single-sensor imaging pipeline. Different design characteristics of various image-enabled consumer electronic devices by the different manufacturers lead to the several arrangements of the color filters in the CFA, affecting both performance and computational efficiency of the demosaicking solution. Extensive experimentation, using ten RGB CFAs and a universal demosaicking framework, reported in this paper indicates that the CFA has a great impact on both the objective and subjective (visual) quality of the demosaicked, full-color image.
It is well-known that the applicability of linear discriminant analysis (LDA) to high-dimensional pattern classification tasks such as face recognition often suffers from the so-called “
small sample ...size” (SSS) problem arising from the small number of available training samples compared to the dimensionality of the sample space. In this paper, we propose a new LDA method that attempts to address the SSS problem using a regularized Fisher’s separability criterion. In addition, a scheme of expanding the representational capacity of face database is introduced to overcome the limitation that the LDA-based algorithms require at least two samples per class available for learning. Extensive experiments performed on the FERET database indicate that the proposed methodology outperforms traditional methods such as Eigenfaces and some recently introduced LDA variants in a number of SSS scenarios.
This paper presents the Secure Shape and Texture SPIHT (SecST-SPIHT) scheme for secure coding of arbitrarily shaped visual objects. The scheme can be employed in a privacy protected surveillance ...system, whereby visual objects are encrypted so that the content is only available to authorized personnel with the correct decryption key. The secure visual object coder employs shape and texture set partitioning in hierarchical trees (ST-SPIHT) along with a novel selective encryption scheme for efficient, secure storage and transmission of visual object shape and textures. The encryption is performed in the compressed domain and does not affect the rate-distortion performance of the coder. A separate parameter for each encrypted object controls the strength of the encryption versus required processing overhead. Security analyses are provided, demonstrating the confidentiality of both the encrypted and unencrypted portions of the secured output bit-stream, effectively securing the entire object shape and texture content. Experimental results showed that no object details are revealed to attackers who do not possess the correct decryption key. Using typical parameter values and output bit-rates, the SecST-SPIHT coder is shown to require encryption on less than 5% of the output bit-stream, a significant reduction in computational overhead compared to "whole content" encryption schemes.
This paper proposes new color local texture features, i.e., color local Gabor wavelets (CLGWs) and color local binary pattern (CLBP), for the purpose of face recognition (FR). The proposed color ...local texture features are able to exploit the discriminative information derived from spatiochromatic texture patterns of different spectral channels within a certain local face region. Furthermore, in order to maximize a complementary effect taken by using both color and texture information, the opponent color texture features that capture the texture patterns of spatial interactions between spectral channels are also incorporated into the generation of CLGW and CLBP. In addition, to perform the final classification, multiple color local texture features (each corresponding to the associated color band) are combined within a feature-level fusion framework. Extensive and comparative experiments have been conducted to evaluate our color local texture features for FR on five public face databases, i.e., CMU-PIE, Color FERET, XM2VTSDB, SCface, and FRGC 2.0. Experimental results show that FR approaches using color local texture features impressively yield better recognition rates than FR approaches using only color or texture information. Particularly, compared with grayscale texture features, the proposed color local texture features are able to provide excellent recognition rates for face images taken under severe variation in illumination, as well as for small- (low-) resolution face images. In addition, the feasibility of our color local texture features has been successfully demonstrated by making comparisons with other state-of-the-art color FR methods.
A postprocessing method for the correction of visual demosaicking artifacts is introduced. The restored, full-color images previously obtained by cost-effective color filter array interpolators are ...processed to improve their visual quality. Based on a localized color ratio model and the original underlying Bayer pattern structure, the proposed solution impressively removes false colors while maintaining image sharpness. At the same time, it yields excellent improvements in terms of objective image quality measures.
Color image zooming on the Bayer pattern Lukac, R.; Plataniotis, K.N.; Hatzinakos, D.
IEEE transactions on circuits and systems for video technology,
11/2005, Letnik:
15, Številka:
11
Journal Article
Recenzirano
Odprti dostop
A zooming framework suitable for single-sensor digital cameras is introduced and analyzed in this paper. The proposed framework is capable of zooming and enlarging data acquired by single-sensor ...cameras that employ the Bayer pattern as a color filter array (CFA). The approach allows for operations on noise-free data at the hardware level. Complexity and cost implementation are thus greatly reduced. The proposed zooming framework employs: 1) a spectral model to preserve spectral characteristics of the enlarged CFA image and 2) an adaptive edge-sensing mechanism capable of tracking the underlying structural content of the Bayer data. The framework readably unifies numerous solutions which differ in design characteristics, computational efficiency, and performance. Simulation studies indicate that the new zooming approach produces sharp, visually pleasing outputs and it yields excellent performance, in terms of both subjective and objective image quality measures.
This paper proposes a novel face descriptor based on color information, i.e., so-called local color vector binary patterns (LCVBPs), for face recognition (FR). The proposed LCVBP consists of two ...discriminative patterns: color norm patterns and color angular patterns. In particular, we have designed a method for extracting color angular patterns, which enables to encode the discriminating texture patterns derived from spatial interactions among different spectral-band images. In order to perform FR tasks, the proposed LCVBP feature is generated by combining multiple features extracted from both color norm patterns and color angular patterns. Extensive and comparative experiments have been conducted to evaluate the proposed LCVBP feature on five public databases. Experimental results show that the proposed LCVBP feature is able to yield excellent FR performance for challenging face images. In addition, the effectiveness of the proposed LCVBP feature has successfully been tested by comparing other state-of-the-art face descriptors.
Mobile terminal location has attracted much interest for its applications in emergency communications, location-sensitive browsing, and resource allocation. The paper introduces the use of ...nonparametric kernel-based estimators for location of mobile terminals using measurements of propagation delays. It is demonstrated that these estimators perform better than the previously used parametric maximum likelihood estimators for the case of a simulated microcell environment with line-of-sight (LOS) and non-line-of-sight (NLOS) radio propagation at several different levels of measurement noise. Their performance is not greatly degraded by NLOS effects. Methods for calculating good values for parameters of the kernel functions are demonstrated, as well as the robustness of the estimators when the values of the parameters vary from the optimal points. A lower bound on the mean square error of location estimation that considers the transition between LOS to NLOS propagation over short distances is presented. It is demonstrated the proposed location estimation method comes close to meeting this bound.
A normalized color-ratio model suitable for color filter array (CFA) interpolation schemes in single-sensor imaging devices are introduced. The first proposed solution utilizes linear shifting of the ...CFA inputs, whereas the second design uses both scaling and shifting operations to normalize color components appearing in the CFA interpolator's input. The utilization of the proposed models can significantly boost the performance of most well-known CFA interpolators. Experimental results indicate that the CFA solutions employing the proposed models exhibits superior performance and eliminates color moire, aliasing and color shifts in the full color camera output.
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