Texture analysis is used in a very broad range of fields and applications, from texture
classification (eg, for remote sensing) to segmentation (eg, in biomedical imaging), passing …

The use of image processing for the detection and classification of defects has been a reality
for some time in science and industry. New methods are continually being presented to …

The rapid growth of digital libraries, e-governance, and internet based applications has
caused an exponential escalation in the volume of 'Big-data'particularly due to texts, images …

Formation of capillary blood vasculature is a critical requirement for native as well as
engineered organs and can be induced in vitro by coculturing endothelial cells with …

Effective characterization of texture images requires exploiting multiple visual cues from the
image appearance. The local binary pattern (LBP) and its variants achieve great success in …

The latest developments in unmanned aerial vehicles (UAVs) and associated sensing
systems make these platforms increasingly attractive to the remote sensing community. The …

In this paper, a novel reduced-reference (RR) image quality assessment (IQA) is proposed
by statistical modeling of the discrete cosine transform (DCT) coefficient distributions. In …

This paper proposes a new approach to extract global image features for the purpose of
texture classification. The proposed texture features are obtained by generating an …

This paper proposes a novel fuzzy model-based unsupervised learning algorithm with
boundary correction for image segmentation. We propose a fuzzy Generalized Gaussian …

Statistical modeling of wavelet subbands has frequently been used for image recognition
and retrieval. However, traditional wavelets are unsuitable for use with images containing …