Searching aligned groups of objects with fuzzy criteria

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Abstract

The detection of aligned groups of objects is important for satellite image interpretation. This task can be challenging when objects have different sizes. In this paper, we propose a method for extracting aligned objects from a labeled image. In this method we construct a neighborhood graph of the objects of the image, and its dual graph where we incorporate information about the relative direction of the objects, evaluated using fuzzy measures of relative position. The groups of objects satisfying the fuzzy criterion of being locally aligned are extracted from the dual graph. These groups are the candidates for being (globally) aligned. The method was tested on synthetic images, and on objects extracted from real images demonstrating that the method extracts the aligned groups of objects even if the objects have different sizes. © 2010 Springer-Verlag Berlin Heidelberg.

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Vanegas, M. C., Bloch, I., & Inglada, J. (2010). Searching aligned groups of objects with fuzzy criteria. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6178 LNAI, pp. 605–613). https://doi.org/10.1007/978-3-642-14049-5_62

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