Watershed Based Document Image Analysis

Document image analysis is used to segment and classify regions of a document image into categories such as text, graphic and background. In this paper we first review existing document image analysis approaches and discuss their limits. Then we adapt the well-known watershed segmentation in order to obtain a very fast and efficient classification. Finally, we compare our algorithm with three others, by running all the algorithms on a set of document images and comparing their results with a ground-truth segmentation designed by hand. Results show that the proposed algorithm is the fastest and obtains the best quality scores.

• Type: Journal
• Year: 2010
• Where: ACIVS
• Authors: Pasha Shadkami, Nicolas Bonnier
• Keywords: ACIVS 2010, Algorithm, Computer Vision, Document Image Analysis, Document Images