Robust Text Detection in Natural Scene Images

Understand

Text detection in natural scene images is an important prerequisite for many content-based image analysis tasks.

• In this paper, we propose an accurate and robust method for detecting texts in natural scene images.
• A fast and effective pruning algorithm is designed to extract Maximally Stable Extremal Regions (MSERs) as character candidates using the strategy of minimizing regularized variations.
• Character candidates are grouped into text candidates by the ingle-link clustering algorithm, where distance weights and threshold of the clustering algorithm are learned automatically by a novel self-training distance metric learning algorithm.