feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of local binary pattern features. in this paper, we investigate the use of local binary patterns for percep...

facial expressions are the most powerful and direct means of presenting human emotions and feelings and offer a window into a persons’ state of mind. in recent years, the study of facial expression and recognition has gained prominence; as industry and services are keen on expanding on the potential advantages of facial recognition technology. as machine vision and artificial intelligence advan...

in this paper we propose a new method for classification of subjects into schizophrenia and control groups using functional magnetic resonance imaging (fmri) data. in the preprocessing step, the number of fmri time points is reduced using principal component analysis (pca). then, independent component analysis (ica) is used for further data analysis. it estimates independent components (ics) of...

Biometric systems based upon finger vein images have been shown to be vulnerable to presentation attacks. In this supplement, we detail a variety of methods extending local binary patterns (LBP) which can be used to distinguish between fake and real finger vein images in terms of description and implementation / experimentation parameters used.

In this paper we evaluate several extensions of Local Binary Patterns to color images. In particular, we investigate their robustness with respect to changes in the illuminant color temperature. To do so, we recovered the spectral reflectances of 1360 texture images from the Outex 13 data set. Then, we rendered the images as if they were taken under 33 different illuminants. For each combinatio...

This paper benchmarks the simple Local Binary Pattern (LBP) approach in the supervised texture segmentation problems of the recent comparative study of Randen and Husøy. A multi-predicate version of LBP is proposed, making our approach even more powerful for images containing textures at multiple scales.

This paper proposes using soft histograms for the Local Binary Pattern (LBP) operator that has been widely applied in different image analysis tasks. This makes the operator more robust to noise and make its output continuous with respect to input. The proposed extension is shown to significantly enhance the performance of the operator with degraded images.