Abstract
In this paper, we propose a method to segment seals and evaluate their quality. Seals with inferior qualities are not suitable for verification. To enhance the robustness of seal system, we put forward a strategy to assess the quality of extracted seal images. First we propose a method to segment seals and get the characters. Then by human assessment, we assign different characters with proper scores as ground-truth. We utilize a series of features and the SVR regression to predict the quality. Finally we use Optical Character Recognition rates to test the effectiveness. Experimental results prove that our proposed method is very effective.
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Wang, C., Hao, Z., Chen, Y. (2013). Blind Quality Assessment on Binary Seal Images . In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_62
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DOI: https://doi.org/10.1007/978-3-642-42057-3_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-42056-6
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