Extracting text from WWW images

Abstract

The authors examine the problem of locating and extracting text from images on the World Wide Web. They describe a text detection algorithm which is based on color clustering and connected component analysis. The algorithm first quantizes the color space of the input image into a number of color classes using a parameter-free clustering procedure. It then identifies text-like connected components in each color class based on their shapes. Finally, a post-processing procedure aligns text-like components into text lines. Experimental results suggest this approach is promising despite the challenging nature of the input data.