Recent advancements in computer vision have enabled wide-ranging applications in every
field of life. One such application area is fresh produce classification, but the classification of …

Imaging flow cytometry has been widely adopted in numerous applications such as optical
sensing, environmental monitoring, clinical diagnostics, and precision agriculture. The …

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 …

Local binary patterns (LBP) are considered among the most computationally efficient high-
performance texture features. However, the LBP method is very sensitive to image noise and …

Abstract Local Binary Patterns (LBP) have emerged as one of the most prominent and
widely studied local texture descriptors. Truly a large number of LBP variants has been …

This paper proposes two sets of novel edge-texture features, Discriminative Robust Local
Binary Pattern (DRLBP) and Ternary Pattern (DRLTP), for object recognition. By …

Most of the local descriptors exists today are based on the relationship between the
neighborhood pixels and the center pixel by considering the 3× 3 spatial window. Moving …

Efficient defect classification is one of the most important preconditions to achieve online
quality inspection for hot-rolled strip steels. It is extremely challenging owing to various …

In this paper, we propose a simple, efficient, yet robust multiresolution approach to texture
classification-binary rotation invariant and noise tolerant (BRINT). The proposed approach is …

Defocus blur is extremely common in images captured using optical imaging systems. It may
be undesirable, but may also be an intentional artistic effect, thus it can either enhance or …