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Automated landmark points detection by using a mixture of approaches: the vole-teeth case

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Abstract

This paper deals with the automated detection of a closed curve’s dominant points. We treat a curve as a 1-D function of the arc length. The problem of detecting dominant points is translated into seeking the extrema of the corresponding 1-D function. Three approaches for automated dominant points detection are presented: (1) an approach based on fitting polynomial, (2) an approach using 1-D computer registration and (3) an innovative approach based on a multi-resolution scheme, zero-crossing and hierarchical clustering. Afterwards, two methods are introduced based on the linearly and non-linearly mixing the results from the three approaches. We then mix the results in a mean-square error sense by using the linear and non-linear fittings, respectively. We experimentally demonstrate the problem of detecting 21 landmarks on 38 vole-teeth that by mixing, the detection accuracy is improved by up to 41.47 % with respect to the results for individual approaches, as applied within the mixture.

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Acknowledgments

The authors gratefully acknowledge the valuable contribution of Assoc. Prof. Dr. Franc Janžekoviè from the Faculty of Natural Sciences and Mathematics, University of Maribor, who provided us with annotated vole-teeth recordings.

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  1. Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ulica 17, 2000 , Maribor, Slovenia

    Božidar Potočnik

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  1. Božidar Potočnik
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Correspondence to Božidar Potočnik.

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Potočnik, B. Automated landmark points detection by using a mixture of approaches: the vole-teeth case. SIViP 9, 93–104 (2015). https://doi.org/10.1007/s11760-012-0414-1

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