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Novel Features for Character Extraction of Historical Chinese Seal Images

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Abstract

Characters in the historical seals is valuable for the research of corresponding documents. Character extraction for these seals is challenging because of the special characteristics of the seals such as the different carving type (rilievi or diaglyph) and variant border form. Thus most existing character extraction methods do not work well with the images of the historical seals. In this paper, a new character extraction method is proposed based on novel features of the scanned seal images. First, the border width feature and structure feature of each scanned seal image are extracted by analysis of the probabilistic density distribution of border width and brightness of each column. Meanwhile, the optimal border width for rilievi or a starting position of border for diaglyph are generated for subsequent border removal and character extraction. The tri-border feature is used to differentiate between diaglyph and tri-border diaglyph. Then a decision tree is built to classify the seal images into rilievi and diaglyph. The classification result is used to divide background, border and character. After the border is removed with the optimal border width estimated from border width feature, the characters are finally extracted from the seal image. Experimental results on the real data set show that the proposed method classifies the scanned seal image accurately and extracts the characters effectively.

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Funding

Funding was provided by Natural Science Foundation of Hunan Province (No. 2018JJ3071).

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  1. College of Electrical and Information Engineering, Hunan University, Changsha, China

    Tingting Dai & Bin Sun

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  1. Tingting Dai
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  2. Bin Sun
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Correspondence to Bin Sun.

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Dai, T., Sun, B. Novel Features for Character Extraction of Historical Chinese Seal Images. Sens Imaging 20, 32 (2019). https://doi.org/10.1007/s11220-019-0253-z

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  • DOI: https://doi.org/10.1007/s11220-019-0253-z

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