Title

Effectiveness of polynomial wavelets in text and image segmentation

Document Type

Article

Publication Date

1-22-2000

Publication Title

Proceedings of SPIE - the International Society for Optical Engineering

Volume

3967

First page number:

259

Last page number:

266

Abstract

Wavelet transforms have been widely used as effective tools in texture segmentation in the past decade. Segmentation of document images, which usually contain three types of texture information: text, picture and background, can be regarded as a special case of texture segmentation. B-spline wavelets possess some desirable properties such as being well localized in time and frequency, and being compactly supported, which make them a good approach to texture analysis. In this paper, cubic B-spline wavelets are applied to document images; thereafter, each texture is featured by several regional and statistical characteristics estimated at the outputs of high frequency bands of spline wavelet transforms. Then three-means classification is applied for classifying pixels which have similar features. We also examine and evaluate the contributions of different factors to the segmentation results from the viewpoints of decomposition levels, frequency bands and feature selection, respectively.

Keywords

Classification--Computer programs; Computer algorithms; Image processing; Spline theory; Wavelets (Mathematics)

Disciplines

Controls and Control Theory | Electrical and Computer Engineering | Electrical and Electronics | Electromagnetics and Photonics

Language

English

Comments

Conference held: San Jose, CA, January 22, 2000

Permissions

Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.

Identifier

DOI: http://dx.doi.org/10.1117/12.373500

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