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Volume: 28 | Article ID: art00004
Comparing object recognition from binary and bipolar edge features
  DOI :  10.2352/ISSN.2470-1173.2016.16.HVEI-111  Published OnlineFebruary 2016

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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Jae-Hyun Jung, Tian Pu, Eli Peli, "Comparing object recognition from binary and bipolar edge featuresin Proc. IS&T Int’l. Symp. on Electronic Imaging: Human Vision and Electronic Imaging,  2016,

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