Text Detection Using MSER and Stroke Width Transform

Text extraction, detection and recognition in images aims at integrating advanced text-based searching technologies which is now recognized as a main component in the development of advanced image and video annotation and retrieval systems. It is also used for image in painting. In this paper, we present a novel algorithm for detecting text in natural and complex images. Basically, it is a two step approach combining maximally stable extremal regions (MSER) and stroke width transformation for the accurate detection of text. Firstly, the MSER image is obtained on which canny edge detection is performed for edge enhancement. To exclude non-text parts, the image is filtered using stroke width information as well as geometric filtering. Experimental results show the effective performance of the proposed method.