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An Information Model for Digital Image Segmentation

  • MATHEMATICAL THEORY OF IMAGES AND SIGNALS REPRESENTING, PROCESSING, ANALYSIS, RECOGNITION, AND UNDERSTANDING
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Abstract

This paper investigates an iterative information-theoretical method for segmentation of digital images. A system that includes a segmentation algorithm with a parameter that determines the number of image segments and a procedure for setting the value of this parameter that minimizes the information redundancy measure is considered. A new simplified mathematical model is proposed to analyze the properties of this system. It is shown that there exists a minimum of the redundancy measure for the proposed model. The adequacy of the model is confirmed experimentally. The computational experiment carried out on images from the Berkeley Segmentation Dataset (BSDS500) shows that a segmented image corresponding to the minimum redundancy measure has the highest informational similarity to ground truth segmentations available in BSDS500. We compared the image segmentation results provided by the EDISON system using the minimum information redundancy criterion and entropy criterion. The advantage of the minimum redundancy criterion is demonstrated.

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Funding

This research was carried out at the Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences in the framework of a state task.

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Authors and Affiliations

  1. Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44/2, Vavilov Street, 119333, Moscow, Russia

    D. M. Murashov

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Correspondence to D. M. Murashov.

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This paper is a completely original work of its author, it has not been published before, and it will not be sent to other publishers until the decision of the PRIA Editorial Board is received.

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The process of writing and the content of the article does not give grounds for raising the issue of a conflict of interest.

Additional information

Dmitry Mikhailovich Murashov. Born January 30, 1958. Graduated from the Ordzhonikidze Moscow Aviation Institute in 1981 (with the specialization of Automatic Control Systems). Received his Candidate’s degree in 1990. Associate Professor in the specialty of Theoretical Foundations of Informatics. He currently works at the Institute of Cybernetics and Educational Informatics of the Federal Research Center “Computer Science and Control” (Russian Academy of Sciences), Moscow. Author of more than 80 papers. Scientific interests: automatic control, image processing and analysis, and pattern recognition.

Translated by Yu. Kornienko

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Murashov, D.M. An Information Model for Digital Image Segmentation. Pattern Recognit. Image Anal. 31, 632–645 (2021). https://doi.org/10.1134/S1054661821040179

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