We build a part-based tree-structured model (TSM) for each category of character.
The TSM utilizes character-specific global structure information.
The TSMs connect detection and recognition together in a certain way.
We propose the normalized pictorial structure framework to recognize words.
The end-to-end system outperforms state-of-the-art methods considerably.