A theoretical tour of connectivity in image processing and analysis Academic Article

abstract

• Connectivity is a concept of great relevance to image processing and analysis. It is extensively used in image filtering and segmentation, image compression and coding, motion analysis, pattern recognition, and other applications. In this paper, we provide a theoretical tour of connectivity, with emphasis on those concepts of connectivity that are relevant to image processing and analysis. We review several notions of connectivity, which include classical topological and graph-theoretic connectivity, fuzzy connectivity, and the theories of connectivity classes and of hyperconnectivity. It becomes clear in this paper that the theories of connectivity classes and of hyperconnectivity unify all relevant notions of connectivity, and provide a solid theoretical foundation for studying classical and fuzzy approaches to connectivity, as well as for constructing new examples of connectivity useful for image processing and analysis applications.

authors

• Braga Neto, Ulisses

published proceedings

• JOURNAL OF MATHEMATICAL IMAGING AND VISION

author list (cited authors)

• Braga-Neto, U., & Goutsias, J.

citation count

• 56

complete list of authors

• Braga-Neto, U||Goutsias, J

publication date

• July 2003

publisher

• Springer Nature  Publisher

published in

• Journal of Mathematical Imaging and Vision  Journal

keywords

• Connectivity Classes
• Fuzzy Connectivity
• Hyperconnectivity
• IMAGE ANALYSIS
• Mathematical Morphology Graph-theoretic Connectivity
• Topological Connectivity

Digital Object Identifier (DOI)

• 10.1023/A:1024476403183

start page

• 5

end page

• 31

volume

• 19

issue

• 1

URL

• http://dx.doi.org/10.1023/a:1024476403183