Finger vein patterns have recently been recognized as an effective biometric identifier and many related work can achieve satisfied results. However, these methods usually suppose the database is non-rotated or slightly rotated, which are strict for preprocessing stages, especially for capture. As we all know, user-friendly capture tends to cause the rotation problem, which degrades the recogni...

An effective rotation and scale invariant log-polar wavelet texture feature for image retrieval was proposed. The feature extraction process involves a log-polar transform followed by an adaptive row shift invariant wavelet packet transform. The log-polar transform converts a given image into a rotation and scale invariant but rowshifted image, which is then passed to the adaptive row shift inv...

The importance of texture analysis and classification in image processing is well known. However, many existing texture classification schemes suffer from a number of drawbacks. A large number of features are commonly used to represent each texture and an excessively large image area is often required for the texture analysis, both leading to high computational complexity. Furthermore, most exi...

Reducing the amount of information stored in diffusion MRI (dMRI) data to a set of meaningful and representative scalar values is a goal of much interest in medical imaging. Such features can have far reaching applications in segmentation, registration, and statistical characterization of regions of interest in the brain, as in comparing features between control and diseased patients. Currently...

More and more attention has been paid to the invariant texture analysis, because the training and testing samples generally have not identical or similar orientations, or are not acquired from the same viewpoint in many practical applications, which often has negative influences on texture analysis. Local binary pattern (LBP) has been widely applied to texture classification due to its simplici...

We propose to apply our recently developed frame-based framework for group-invariant morphology to the problem of tensor field morphology. Group invariance (and particularly rotation invariance) have been, and are, motivated to be relevant for filtering tensor fields. This leads to the development of a rotation-invariant frame for tensors, which can be used to easily define rotation-invariant m...

Classification of texture images, especially those with different orientation and scale changes, is a challenging and important problem in image analysis and classification. This paper proposes an effective scheme for rotation and scale invariant texture classification using log-polar wavelet signatures. The rotation and scale invariant feature extraction for a given image involves applying a l...

In this paper, we present a theoretically and computationally simple but efficient approach for rotation invariant texture classification. This method is based on new texture signatures extracted from spectrum. Rotation invariant texture features are obtained based on the extension of the derived signatures. The features are tested with 1000 randomly rotated samples of 20 Brodatz texture classe...

Several important pattern recognition applications are based on feature extraction and vector clustering. Directional patterns may be represented by rotation-variant directional vectors, formed from M features uniformly extracted in M directions. It is often required that pattern recognition algorithms are invariant under pattern rotation or, equivalently, invariant under circular shifts of suc...

This paper presents a new approach of rotation invariant texture analysis. Robust rotation invariant textures are important for digital image libraries and multimedia database. Here a method for application of rotation variant Traditional Gabor Filter (TGF) for rotation invariant texture analysis is presented. The orientation of the texture is determined using radon transformation. Once the rot...