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Scale-space color blob and ridge detection

  • Representation, Processing, Analysis and Understanding of Images
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Abstract

Feature detection in color images frequently consists in image conversion from color to grayscale and then one of grayscale detectors application. This approach has a few disadvantages: some features become indistinguishable in grayscale and features ordering based on response of grayscale detector do not accord with features order of importance from human’s perception point of view. There are two essential contributions in this paper. First, the method for direct detection of blobs and ridges in color images is proposed. Second, for scale-space ridge detection we introduce a 3D non maxima suppression procedure (in two orthogonal directions) which makes ridge detection simple and easy programmable in contrast to Lindeberg’s automatic scale selection approach. The proposed algorithms also produce estimates of blobs sizes and ridges width.

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Authors and Affiliations

  1. Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Leninskie gory 1, build. 2, Moscow, 119991, Russia

    N. A. Khanina, E. V. Semeikina & D. V. Yurin

Authors
  1. N. A. Khanina
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  2. E. V. Semeikina
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  3. D. V. Yurin
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Correspondence to N. A. Khanina.

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The article was translated by the authors.

Natalia Alekseevna Khanina (1989), student, Chair of Mathematical Physics, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Russia.

Ekaterina Victorovna Semeikina (1987), PhD student, Chair of Mathematical Physics, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Russia.

Dmitry Vladimirovich Yurin (1965), PhD, senior researcher at laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Russia.

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Khanina, N.A., Semeikina, E.V. & Yurin, D.V. Scale-space color blob and ridge detection. Pattern Recognit. Image Anal. 22, 221–227 (2012). https://doi.org/10.1134/S1054661812010221

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  • DOI: https://doi.org/10.1134/S1054661812010221

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