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 …

Since traditional frequent pattern mining approaches assume that all the items in binary
databases have the same importance regardless of their own features, they have difficulty in …

In the past few years, the research studies in image-based shape representation have been
proliferating due to its usefulness and importance for various application. This field has been …

Shape is known as an important source of information in object analyzes and has been
studied for many years for this context. In the object classification task, several challenges …

In this paper, we propose two novel textural-based features for writer identification: CoHinge
and QuadHinge which are based on the spatial and attribute co-occurrence of the Hinge …

In many engineering and medical imaging fields, shape, and margin descriptors play an
important role in challenging pattern recognition and classification problems. This paper …

Linear discriminant analysis (LDA) with its extensions is a group of classical methods in
dimensionality reduction for supervised learning. However, when some classes are far away …

In this paper, we define a new fuzzy squareness measure to quantify how much a given
fuzzy shape matches a fuzzy square. The new fuzzy shape-based measure is naturally …

Shape classification from binary images is a challenging task within the computer vision
community. Commonly, contour and structural features are computed to describe the objects …

Contour segment (CS) is the fundamental element of partial boundaries or edges in shapes
and images. So far, CS has been widely used in many applications, including object …