Conventional Gabor representation and its extracted features often yield a fairly poor performance in retrieving the rotated and scaled versions of the texture image under query. To address this issue, existing methods exploit multiple stages of transformations for making rotation and/or scaling being invariant at the expense of high computational complexity and degraded retrieval performance. ...

Local Parameter Histograms (LPH) based on Gaussian Markov random fields (GMRFs) have been successfully used in effective texture discrimination. LPH features represent the normalized histograms of locally estimated GMRF parameters via local linear regression. However, these features are not rotation invariant. In this paper two techniques to design rotation invariant LPH texture descriptors are...

Farsi Handwriting Word Recognition (FHWR), especially those with different orientation and scale changes as well as different handwriting style, is a challenging and important problem in document image analysis. This paper proposes a holistic FHWR scheme using local features of M-Band packet wavelet. The rotation and scale invariant local feature extraction for a given word image involves apply...

Orthoimages are aerial images where feature displacements and scale variations have been removed. This type of images is widely used to calculate areas, determine land cover and land use, among others. This paper introduces a rotation-invariant classification model for three common orthoimage regions: city, sea and forest areas, using only texture information (without color information). Our cl...

We present a novel image feature descriptor for rotationally invariant 2D texture classification. This extends our previous work on noise-resistant and intensity-shift invariant median binary patterns (MBPs), which use binary pattern vectors based on adaptive median thresholding. In this paper the MBPs are hashed to a binary chain or equivalence class using a circular bit-shift operator. One bi...

Many image-rotation invariant texture classification approaches have been presented. However, image rotation is not necessarily the same as surface rotation. This paper proposes a novel scheme that is surface-rotation invariant. It uses magnitude spectra of the partial derivatives of the surface obtained using photometric stereo. Unfortunately the partial derivative operator is directional. It ...