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

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.

Research highlights► A novel detector of shift-invariant image location is presented. ► Experiments show its high-precision, robustness, and low-noise. ► It leads to a wide range of novel image-to-‘data structures’ processing algorithms. ► An image constructed inversely by the structures resembles strongly the original. ► Analysis of the complexity and a comparison with Canny’s detector is presented.