Categorizing Texture plays a central role in performing automated machine vision tasks
such as defect detection and visual inspectionin industries and factories. Classifying texture …

Active contour models (ACMs) have been widely used in image segmentation to segment
objects. However, when it comes to segmenting images with severe intensity …

Texture recognition is one of the most important tasks in computer vision, with numerous
applications in several areas. Despite the recent success of end-to-end deep learning …

Active contour models (ACMs) are popular and widely used for many image segmentation
applications and obtain promising results. However, these methods are unable to achieve …

In this paper, a blind semi-fragile dual watermarking system for video content authentication
and tampering localization is proposed. In this method, two watermarks are tailored for each …

Information from an image occurs over multiple and distinct spatial scales. Image pyramid
multiresolution representations are a useful data structure for image analysis and …

Objectives Following the craze for radiomic features (RF), their lack of reliability raised the
question of the generalizability of classification models. Inter-site harmonization of images …

Texture can be defined as the change of image intensity that forms repetitive patterns
resulting from the physical properties of an object's roughness or differences in a reflection …

This paper ideates a novel texture descriptor that retains its classification accuracy under
varying conditions of image orientation, scale, and illumination. The proposed Overlapped …

Visual scene recognition is predominantly based on visual textures representing an object's
material properties. However, the single material texture varies in scale and illumination …