Document Segmentation Using Polynomial Spline Wavelets

Document Type

Article

Publication Date

12-2001

Publication Title

Proceedings of SPIE - the International Society for Optical Engineering

Volume

34

Issue

12

First page number:

2533

Last page number:

2545

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 an effective tool for texture analysis. Based on the observation that text textures provide fast-changed and relatively regular distributed edges in the wavelet transform domain, an efficient document segmentation algorithm is designed via cubic B-spline wavelets. Three-means or two-means classification is applied for classifying pixels with similar characteristics after feature estimation at the outputs of high frequency bands of spline wavelet transforms. We examine and evaluate the contributions of different factors to the segmentation results from the viewpoints of decomposition levels, frequency bands and wavelet functions. Further performance analysis reveals the advantages of the proposed method.

Keywords

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

Disciplines

Electrical and Computer Engineering | Engineering | Signal Processing

Language

English

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.

UNLV article access

Search your library

Share

COinS