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GMD: geometric model-based local binary descriptor

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Abstract

Many researchers focused on binary descriptor due to its low computational power. It is an adequate solution for embedded systems. The previous works on the elaboration of binary descriptor did not exploit all information brought by a patch. The authors used just the pixel intensities to generate a binary test, so these descriptors lack efficiency on patch description. In this paper, we design a new descriptor named Geometric Model Descriptor (GMD) based on intensity and geometric coordinate of the pixel. We divide the patch into a grid cell (sub-patches); then each sub-patch is augmented in dimension (being 3D) by considering the intensity as the third dimension rather than its two dimensions (2D) form. Based on geometric modeling (polynomial interpolation and Bezier curve), we interpolate the cloud of points to find an approximation of the geometric model for each sub-patch. A binary test will be performed between the coefficients of sub-patch models to generate the patch description. The deep evaluation of GMD on a benchmark data set shows a high discrimination in the presence of similarity. The GMD exhibits robustness and reliability against severe changes. A computation costing is reported in the results section by presenting a compromise between accuracy and real-time constraint.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Polytechnic School, 10 Avenue Hassen Badi BP 182 El Harrach, 16200, Algiers, Algeria

    Kobzili Elhaouari & Larbes Cherif

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  1. Kobzili Elhaouari
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  2. Larbes Cherif
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Correspondence to Kobzili Elhaouari.

Additional information

Kobzili Elhaouari is currently a Ph.D. student at ENP of Algiers. Larbes Cherif is a full professor at ENP of Algiers.

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Elhaouari, K., Cherif, L. GMD: geometric model-based local binary descriptor. SIViP 13, 289–297 (2019). https://doi.org/10.1007/s11760-018-1356-z

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  • DOI: https://doi.org/10.1007/s11760-018-1356-z

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