Comparing Object Recognition from Binary and Bipolar Edge Features

Overview

Journal IS&T Int Symp Electron Imaging

Date 2017 Apr 15

PMID 28409188

Authors

Jae-Hyun Jung

Tian Pu

Eli Peli

Affiliations

Soon will be listed here.

Abstract

Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary edge images (black edges on white background or white edges on black background) have been used to represent features (edges and cusps) in scenes. However, the polarity of cusps and edges may contain important depth information (depth from shading) which is lost in the binary edge representation. This depth information may be restored, to some degree, using bipolar edges. We compared recognition rates of 16 binary edge images, or bipolar features, by 26 subjects. Object recognition rates were higher with bipolar edges and the improvement was significant in scenes with complex backgrounds.

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