Unconstrained logo detection in document images

作者:

Highlights:

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.

论文关键词:Logo detection,Document imaging,Segmentation,Mountain function

论文评审过程:Accepted 25 February 2003, Available online 30 May 2003.

论文官网地址:https://doi.org/10.1016/S0031-3203(03)00125-0