Scene text detection with extremal region based cascaded filtering
Gen Li, Jie Liu, Shuwu Zhang, Yang Zheng · 2016
In this paper, we present a robust Extremal Region (ER) based scene text detection system. To eliminate the vast non-text components generated by ER operator, a three-stage cascaded filter is proposed. In the first stage, a powerful character classifier enhanced by recursive local search is introduced to separate text components from noises. Then, an efficient heuristic pruning method is designed to further clean overlapped duplicate characters. Finally, after text line construction, a cascaded text line classification model integrating word entropy and sliding window based CNN is proposed to remove false text lines. Experiments on benchmarks show that our method achieves state-of-the-art performance.