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Comparison of Corner Detectors for Revolving Objects Matching Task

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7267)

Abstract

The paper contains test of corner detectors applied in finding characteristic points on 3D revolving objects. Five different algorithm are presented starting from historical Moravec detector and ending at newest ones, such as SUSAN and Trajkovic.

Since the algorithms are compared from the perspective of use for 3D modeling, the count of detected points and their localization is compared. The modeling process uses a series of photos and requires finding a projection of 3D point to two or three subsequent photos. The quality of algorithms is discussed on the base of the ability to detect modeled objects’ corners and immunity to noise. The last researched aspect is the computation cost.

The presented tests show that the best results are given by Shi–Tomasi operator. The detector does find false corners on noisy images, thus SUSAN operator may be used instead.

Keywords

  • Computer vision
  • Corner detectors
  • 3D modeling

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References

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© 2012 Springer-Verlag Berlin Heidelberg

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Bagrowski, G., Luckner, M. (2012). Comparison of Corner Detectors for Revolving Objects Matching Task. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_53

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  • DOI: https://doi.org/10.1007/978-3-642-29347-4_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29346-7

  • Online ISBN: 978-3-642-29347-4

  • eBook Packages: Computer ScienceComputer Science (R0)