Algorithms for adaptive transform edge detection

Author

Sundaram, Ravi

Author_Institution

Information Syst. Inc., West Lafayette, IN

Volume

47

Issue

8

fYear

1999

fDate

8/1/1999 12:00:00 AM

Firstpage

2313

Lastpage

2317

Abstract

Edge detection in grayscale digital images based on the locations of zero crossings has been investigated. Samples of the image are transformed using the discrete symmetric cosine transform (DSCT) and filtered using truncated time or frequency sampled forms of the Laplacian-of-Gaussian (LOG) filter. This article presents and evaluates adaptive block-based filtering procedures to localize edges based on discrete circular and real transforms. Measures of the signal-to-noise ratio (SNR) and edge localization are provided

Keywords

adaptive filters; adaptive signal processing; discrete cosine transforms; edge detection; filtering theory; image sampling; DSCT; Laplacian-of-Gaussian filter; SNR measures; adaptive block-based filtering; adaptive transform edge detection; algorithms; discrete circular transform; discrete real transform; discrete symmetric cosine transform; edge localization; grayscale digital images; image samples; linear convolution; signal-to-noise ratio; truncated frequency sampled filter; truncated time filter; zero crossings location; Adaptive filters; Band pass filters; Convolution; Digital images; Discrete transforms; Filtering theory; Frequency; Image edge detection; Sampling methods; Signal to noise ratio;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.774776

Filename

774776