A synopsis of recentwork in edge detection using the DWT

Author

Brannock, Evelyn ; Weeks, Michael

Author_Institution

Georgia State Univ., Atlanta

fYear

2008

fDate

3-6 April 2008

Firstpage

515

Lastpage

520

Abstract

Automatic edge detection is a highly researched field because it is used in many different applications in image processing, such as diagnosis in medical imaging, topographical recognition and automated inspection of machine assemblies. Historically, the Discrete Wavelet Transform (DWT) has been a successful technique used in edge detection. The contributions of new, recent work in this area are examined and summarized concisely. Utilizing multiple phases, such as de-noising, preprocessing, thresholding coefficients, smoothing, and postprocessing, are suggested for use with multiple iterations of the DWT in this research. The DWT is combined with various other methods for an optimal solution for the edge detection problem. This synopsis consolidates recent, related work into one source.

Keywords

discrete wavelet transforms; edge detection; image denoising; image segmentation; smoothing methods; DWT; automatic edge detection; discrete wavelet transform; image de-noising; image postprocessing; image preprocessing; image smoothing; image thresholding coefficients; Biomedical imaging; Computer science; Detectors; Discrete wavelet transforms; Filters; Image edge detection; Image processing; Image recognition; Noise reduction; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Southeastcon, 2008. IEEE

Conference_Location

Huntsville, AL

Print_ISBN

978-1-4244-1883-1

Electronic_ISBN

978-1-4244-1884-8

Type

conf

DOI

10.1109/SECON.2008.4494349

Filename

4494349