Exploiting the synergy between fractal dimension and lacunarity for improved texture recognition

DOI10.1016/J.SIGPRO.2011.04.018zbMath1221.68223OpenAlexW2028907076MaRDI QIDQ635060

Rahib Hidayat Abiyev, Kemal Ihsan Kilic

Publication date: 19 August 2011

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2011.04.018

zbMATH Keywords

fractal dimensionLevenberg-Marquardt methodtexture recognitionlacunaritygliding-boxsummed area table

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05)

Related Items (5)

Texture classification using non-Euclidean Minkowski dilation ⋮ A novel neural network based image descriptor for texture classification ⋮ Weighted fusion of MRI and PET images based on fractal dimension ⋮ Shape classification by manifold learning in multiple observation spaces ⋮ Discrete Schroedinger transform for texture recognition

Uses Software

• KELLEY

Cites Work

• On the quadratic mapping \(z\rightarrow z^{2}-\mu \) for complex \(\mu \) and \(z\): the fractal structure of its set, and scaling
• Lacunarity definition for ramified data sets based on optimal cover
• A robust algorithm for the fractal dimension of images and its applications to the classification of natural images and ultrasonic liver images
• An improved box-counting method for image fractal dimension estimation
• Unnamed Item

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