Auto Secured Text Monitor in Natural Scene Images

Abstract

Monitoring the text in content based images is an important task. An accurate and robust method to monitor texts in natural scene images. In this paper fast and effective decision tree algorithm (MSERs) is used to extract a character participant by reducing regularized character dissimilarities. Character participant are grouped into text participant by using single-link clustering algorithm. Text participant with high non-text probabilities are removed and texts are establish with a text classifier. Valuable information may be broken in many content-based images, such as web images. We need to detect text before recognizing and retrieving.