Wavelet based automatic thresholding for image segmentation

Author

Zhang, Xiao-Ping ; Desai, Mita D.

Author_Institution

Div. of Eng., Texas Univ., San Antonio, TX, USA

Volume

1

fYear

1997

fDate

26-29 Oct 1997

Firstpage

224

Abstract

In this paper, a new systematic method to segment possible target areas based on wavelet transforms is presented. We develop an analytic model for the segmentation of targets, which uses a novel multiresolution analysis in concert with a Bayesian classifier to identify the possible target areas. A method is developed which adaptively chooses thresholds to segment targets from background, by using a multiscale analysis of the image probability density function (PDF). We present examples which demonstrate the efficiency of the technique on a variety of targets

Keywords

Bayes methods; image classification; image resolution; image segmentation; probability; wavelet transforms; Bayesian classifier; analytic model; automatic thresholding; image segmentation; multiresolution analysis; multiscale analysis; probability density function; systematic method; target areas segmentation; wavelet transforms; Bayesian methods; Image analysis; Image edge detection; Image segmentation; Multiresolution analysis; Neoplasms; Pixel; Probability distribution; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1997. Proceedings., International Conference on

Conference_Location

Santa Barbara, CA

Print_ISBN

0-8186-8183-7

Type

conf

DOI

10.1109/ICIP.1997.647744

Filename

647744