Patent ID: 9042645
Filing Date: 2015-05-26
Classification: G06K

Abstract:
1. A method for detecting features in digital numeric data, the method comprising: obtaining, by a processing unit, digital numeric data comprising values corresponding to a plurality of sampling points over a domain space having at least one dimension; computing, by the processing unit, a plurality of scale-space data, each of the plurality of scale-space data comprising data over the domain space at a corresponding scale in the domain space, wherein the computing of the plurality of scale-space data comprises filtering the digital numeric data using a filter bank; determining, by the processing unit, a plurality of feature regions in the plurality of scale-space data, each feature region corresponding to a local extremum in scale and location of the scale-space data; and determining, by the processing unit, a feature region descriptor for each of the plurality of feature regions; wherein the filter bank is a Cosine Modulated Gaussian filter bank in which a standard deviation parameter of the Gaussian equals multiplied by a cosine wavelength, in which b is in the range of 0.75 to 1.25, or the filter bank is an N th -order Gaussian Derivative filter bank with N being in the range of 5 to 20.