Unconstrained logo detection in document images

被引：33

作者：

Pham, TD ^{[1
]}

机构：

[1] Griffith Univ, Sch Comp & Informat Technol, Brisbane, Qld 4111, Australia

来源：

PATTERN RECOGNITION | 2003年 / 36卷 / 12期

关键词：

logo detection; document imaging; segmentation; mountain function;

D O I：

10.1016/S0031-3203(03)00125-0

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A fast and effective algorithm is developed for detecting logos in grayscale document images. The computational schemes involve segmentation, and the calculation of the spatial density of the defined foreground pixels. The detection does not require training and is unconstrained in the sense that the presence of a logo in a document image can be detected under scaling, rotation, translation, and noise. Several tests on different electronic document forms such as letters, faxes, and billing statements are carried out to illustrate the performance of the method. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

引用

页码：3023 / 3025

页数：3