A new pivoting and iterative text detection algorithm for biomedical images.

ABSTRACT: There is interest to expand the reach of literature mining to include the analysis of biomedical images, which often contain a paper's key findings. Examples include recent studies that use Optical Character Recognition (OCR) to extract image text, which is used to boost biomedical image retrieval and classification. Such studies rely on the robust identification of text elements in biomedical images, which is a non-trivial task. In this work, we introduce a new text detection algorithm for biomedical images based on iterative projection histograms. We study the effectiveness of our algorithm by evaluating the performance on a set of manually labeled random biomedical images, and compare the performance against other state-of-the-art text detection algorithms. We demonstrate that our proje

SUBMITTER: Xu S 

PROVIDER: S-EPMC3265968 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature