Palmprint recognition, as a new branch of biometric technology, has attracted much attention in recent years. Various palmprint representations have been proposed for recognition. Gabor feature has been recognized as one of the most effective representations for palmprint recognition, where Gabor phase and orientation feature representations are extensively studied. In this paper, we explore a ...

Gabor filtering is useful for intelligent image processing, but it requires huge computational power. Its pixel-parallel LSI implementation is one solution for real-time image processing. This paper proposes a new Gabor filtering algorithm using a discrete-time cellular neural network (CNN) circuit, which is suitable for pixel-parallel LSI implementation. The proposed algorithm utilizes transie...

Steerable properties dominate the design of traditional filters, e.g., Gabor filters, and endow features the capability of dealing with spatial transformations. However, such excellent properties have not been well explored in the popular deep convolutional neural networks (DCNNs). In this paper, we propose a new deep model, termed Gabor Convolutional Networks (GCNs or Gabor CNNs), which incorp...

Biometrics is the science and technology of measuring and analyzing biological data. In information technology, biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns, facial patterns and hand measurements for authentication purposes. Fingerprint is one of the most developed biometrics, with more h...

Gabor filters have been successfully employed in texture segmentation problems, yet a general multi-filter multi-texture Gabor filter design procedure has not been offered. To this end, we first present a multichannel paradigm that provides a mathematical framework for the design of the filters. The paradigm establishes relationships between the predicted texture-segmentation error, the power s...

Gabor frames {e2πinβ·xg(x− kα)}n,k∈Zd provide series representations not only of functions in L(R) but of the entire range of spaces M ν known as the modulation spaces. Membership of a function or distribution f in the modulation space is characterized by a sequence-space norm of the Gabor coefficients of f depending only on the magnitudes of those coefficients, and the Gabor series representat...

We introduce a systematic approach to the design, implementation and analysis of left-invariant evolution schemes acting on Gabor transform, primarily for applications in signal and image analysis. Within this approach we relate operators on signals to operators on Gabor transforms. In order to obtain a translation and modulation invariant operator on the space of signals, the corresponding ope...

In this paper, a new technique called Two Dimensional Gabor Fisher Discriminant (2DGFD) is derived and implemented for image representation and recognition. In our approach, the Gabor wavelets are used to extract facial features. The Principal Component Analysis (PCA) is applied directly on the Gabor transformed matrices to remove redundant information from the image rows and a new direct two d...

Gabor-based face representation has achieved enormous success in face recognition. This research addresses a hybrid neural network solution for face recognition trained with Gabor features. The system is commenced on convolving a face image with a series of Gabor filter coefficients at different scales and orientations. The neural network employed for face recognition is based on BAM for dimens...

We present a method that analyzes a two-dimensional magnitude spectrogram S(f, t) into its local constituent spectro-temporal amplitudes A(f, t), frequencies F (f, t), orientations Θ(f, t), and phases φ(f, t). The method operates by performing a twodimensional local Gabor-like analysis of the spectrogram, retaining only the parameters of the 2D-Gabor filter with maximal amplitude response withi...