Texture is a fundamental characteristic of many types of images, and texture representation
is one of the essential and challenging problems in computer vision and pattern recognition …

Automatic detection and localization of anomalies in nanofibrous materials help to reduce
the cost of the production process and the time of the post-production visual inspection …

We propose a new dataset for the evaluation of food recognition algorithms that can be used
in dietary monitoring applications. Each image depicts a real canteen tray with dishes and …

Grey‐level co‐occurrence matrix (GLCM) is a widely used texture feature descriptor that is
extracted from grey‐level images. A considerable amount of work in the literature has been …

Obesity is increasing worldwide and can cause many chronic conditions such as type-2
diabetes, heart disease, sleep apnea, and some cancers. Monitoring dietary intake through …

We demonstrate a simple and effective automated method for the localization of glomeruli in
large (~ 1 gigapixel) histopathological whole-slide images (WSIs) of thin renal tissue …

Aiming at the defect of Local Binary Pattern (LBP) and its variants, this paper presents a new
modeling of the conventional LBP operator for texture classification. Named Attractive-and …

Convolutional Neural Networks (CNN) have brought spectacular improvements in several
fields of machine vision including object, scene and face recognition. Nonetheless, the …

Colour and texture are two perceptual stimuli that determine, to a great extent, the
appearance of objects, materials and scenes. The ability to process texture and colour is a …

The aim of this work is to predict the complexity perception of real world images. We propose
a new complexity measure where different image features, based on spatial, frequency and …