Zoom-Invariant Vision of Figural Shape: The Mathematics of Cores

• Published in: Computer vision and image understanding Vol. 69; no. 1; pp. 55 - 71
• Main Authors: Pizer, Stephen M., Eberly, David, Fritsch, Daniel S., Morse, Bryan S.
• Format: Journal Article
• Language: English
• Published: San Diego, CA Elsevier Inc 01.01.1998; Elsevier
• Subjects: Algorithmics. Computability. Computer arithmetics; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Pattern recognition. Digital image processing. Computational geometry; Theoretical computing; Invariant; Image analysis; Approximation; Segmentation; Image processing; Differential equation; Noise reduction; Algorithm; Pattern extraction
• ISSN: 1077-3142; 1090-235X
• DOI: 10.1006/cviu.1997.0563

Believing that figural zoom invariance and the cross-figural boundary linking implied by medial loci are important aspects of object shape, we present the mathematics of and algorithms for the extraction of medial loci directly from image intensities. The medial loci called cores are defined as generalized maxima in scale space of a form of medial information that is invariant to translation, rotation, and, in particular, zoom. These loci are very insensitive to image disturbances, in strong contrast to previously available medial loci, as demonstrated in a companion paper. Core-related geometric properties and image object representations are laid out which, together with the aforementioned insensitivities, allow the core to be used effectively for a variety of image analysis objectives.