Binarizing Business Card Images for Mobile Devices

TL;DR

This paper introduces a fast, adaptive binarization method tailored for camera-captured business card images on mobile devices, effectively handling diverse graphics and text for improved processing.

Contribution

The paper presents a novel, efficient binarization technique specifically designed for mobile device images of business cards, addressing challenges of varied content and background complexity.

Findings

The method is fast and suitable for mobile devices.

It effectively separates text from complex backgrounds.

The technique improves binarization accuracy for business card images.

Abstract

Business card images are of multiple natures as these often contain graphics, pictures and texts of various fonts and sizes both in background and foreground. So, the conventional binarization techniques designed for document images can not be directly applied on mobile devices. In this paper, we have presented a fast binarization technique for camera captured business card images. A card image is split into small blocks. Some of these blocks are classified as part of the background based on intensity variance. Then the non-text regions are eliminated and the text ones are skew corrected and binarized using a simple yet adaptive technique. Experiment shows that the technique is fast, efficient and applicable for the mobile devices.