Feature descriptors using super-pixels as fuzzy numbers

Abstract

The objective of this paper is to extract directly local important region descriptors using image super-pixels and fuzzy numbers. Previous works are based on extracting important feature points like corners in an image then region descriptors are formed around these features. Our novel contribution is to consider directly the most discriminative super-pixels as region descriptors. First, each super-pixel is considered as a fuzzy number. Then the alpha-cut which best represents the fuzzy number is obtained. Finally, according to these alpha-cuts and the cardinality of each fuzzy number the region descriptors are formed. Matching is done according to distances between fuzzy numbers. The Palm-print recognition problem was chosen to show the effectiveness of this approach.