Weighted least squares method for the approximation of directional derivatives

Author

Tico, Marius ; Kuosmanen, Pauli

Author_Institution

Digital Media Inst., Tampere Univ. of Technol., Finland

Volume

3

fYear

2001

fDate

2001

Firstpage

1681

Abstract

Using the facet model we design a family of filters for the approximation of partial derivatives of the digital image surface. Prior information (e.g., local dominant orientation) is incorporated in a two-dimensional weight function. A weighted least squares estimation of the facet parameters is applied in order to design the proposed filters. Exemplary application of the proposed filters to fingerprint image segmentation is also presented

Keywords

filtering theory; fingerprint identification; image segmentation; least squares approximations; parameter estimation; digital image surface; directional derivative approximation; facet model; facet parameters; filters; fingerprint image segmentation; local dominant orientation; partial derivative approximation; two dimensional weight function; weighted least squares estimation; Application software; Digital images; Face detection; Fingerprint recognition; Image segmentation; Least squares approximation; Least squares methods; Optical filters; Polynomials; Surface topography;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on

Conference_Location

Salt Lake City, UT

ISSN

1520-6149

Print_ISBN

0-7803-7041-4

Type

conf

DOI

10.1109/ICASSP.2001.941261

Filename

941261