Abstract
An approach is presented for characterize objects and image texture by local lacunarity. This measure makes possible to distinguish sets that have same fractal dimension. In image analysis it can be used as a new feature in the pattern recognition process mainly for identification of natural textures. Illustrating the approach, two types of examples were presented: 3D objects representing approximations of fractal sets and medical images. In the first type, we apply this approach to show its possibility when the objects presents the same fractal dimension. The second type shows that it can be used as a feature on pattern recognition alone in many resolutions.
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de Melo, R.H.C., de A. Vieira, E., Conci, A. (2006). Characterizing the Lacunarity of Objects and Image Sets and Its Use as a Technique for the Analysis of Textural Patterns. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_19
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DOI: https://doi.org/10.1007/11864349_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44630-9
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