Character pattern extraction based on local multilevel thresholding and region growing

Hideaki Goto, Hirotomo Aso

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Recent remarkable progress in computer systems and printing devices makes it easier to produce printed documents with various designs. Text characters are often printed on colored backgrounds, and sometimes on complex backgrounds. Some methods have been developed for character extraction from document images and scene images with complex backgrounds. However, those methods are designed to extract rather large characters, and often fails to extract small characters. This paper proposes a new method by which character patterns can be extracted from document images with complex background. The method is based on the local multilevel thresholding and pixel labeling, and the region growing. This framework is very useful for extracting character patterns from badly illuminated document images. The performance of extracting small character patterns has also been improved by suppressing the influence of mixed-color pixels around character edges.

Original languageEnglish
Pages (from-to)430-433
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Volume15
Issue number4
Publication statusPublished - 2000 Dec 1

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Character pattern extraction based on local multilevel thresholding and region growing'. Together they form a unique fingerprint.

Cite this