A scalable, high-precision, and low-noise detector of shift-invariant image locations

Authors:
Georgii Khachaturov
Affiliations:
Departamento de Sistemas, Universidad Autónoma Metropolitana, Av. San Pablo 180, Col. Reynosa Tamaulipas, C.P. 02200, D.F., Mexico
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

A scalable, high-precision, and low-noise detector of shift invariant locations in grayscale images is presented. It leads to a wide range of novel image-to-'data structures' processing algorithms. Experiments with a single algorithm of this range prove that (i) the output structures convey great amount of semantically relevant information about the original image; (ii) this information can be successfully extracted and used in subsequent applications.