CVNov 12, 2014

Amoeba Techniques for Shape and Texture Analysis

arXiv:1411.3285v21 citations
Originality Synthesis-oriented
AI Analysis

This is an incremental review paper summarizing existing work on morphological amoebas for image processing researchers.

This paper reviews morphological amoebas, which are image-adaptive structuring elements for local image filters that combine spatial distance with contrast information, and explores their connections to PDE-based filtering methods and applications in texture analysis.

Morphological amoebas are image-adaptive structuring elements for morphological and other local image filters introduced by Lerallut et al. Their construction is based on combining spatial distance with contrast information into an image-dependent metric. Amoeba filters show interesting parallels to image filtering methods based on partial differential equations (PDEs), which can be confirmed by asymptotic equivalence results. In computing amoebas, graph structures are generated that hold information about local image texture. This paper reviews and summarises the work of the author and his coauthors on morphological amoebas, particularly their relations to PDE filters and texture analysis. It presents some extensions and points out directions for future investigation on the subject.

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