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Using fractal features of digital images for the detection of surface defects

  • Representation, Processing, Analysis and Understanding of Images
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Abstract

The self similarity of a digital image is described. New image features that characterize the internal distribution of self similarity and the image segments with the highest similarity are proposed. An algorithm for generating fractal features of images (characteristic image segments and self-similarity distribution) is described. The results of investigating the possibility of using the self-similarity distribution in image classification problems are presented.

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Authors and Affiliations

  1. Murom Institute (Branch), Vladimir State University, ul. Orlovskaya 23, Murom, 602264, Russia

    A. L. Zhiznyakov, D. G. Privezentsev & A. A. Zakharov

Authors
  1. A. L. Zhiznyakov
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  2. D. G. Privezentsev
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  3. A. A. Zakharov
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Corresponding author

Correspondence to A. L. Zhiznyakov.

Additional information

This paper uses the materials of a report that was submitted at the 11th International Conference Pattern Recognition and Image Analysis: New Information Technologies that was held in Samara, Russia on September 23–28, 2013.

Arkadii L’vovich Zhiznyakov. Received doctoral degree. Professor and Head of the Department of CAD systems of the Murom Institute (Branch) of Vladimir State University. First Deputy Director of the Murom Institute (Branch) of Vladimir State University. Author of more than 180 papers. Scientific interests: digital image processing.

Denis Gennad’evich Privezentsev. Received candidate’s degree. Associate Professor at the Department of CAD systems of the Murom Institute (Branch) of Vladimir State University. Author of 35 papers. Scientific interests: digital image processing.

Aleksei Aleksandrovich Zakharov. Received candidate’s degree. Associate Professor at the Department of IS of the Murom Institute (Branch) of Vladimir State University. Author of 40 papers. Scientific interests: digital image processing.

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Zhiznyakov, A.L., Privezentsev, D.G. & Zakharov, A.A. Using fractal features of digital images for the detection of surface defects. Pattern Recognit. Image Anal. 25, 122–131 (2015). https://doi.org/10.1134/S105466181501023X

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  • DOI: https://doi.org/10.1134/S105466181501023X

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