@inproceedings{f3554c48a2ff46ecad26a2a4d822bd37,
title = "Handwriting signature identification based on improved adaptive median filtering algorithm",
abstract = "Handwritten signature is widely used for human identity authentication in daily life. In order to improve the recognition accuracy and promote the success rate, it is necessary to preprocess the signature image. In this paper, the signature image preprocessing included smooth filtering, image binaryzation, signature area acquisition, and edge thinning. Furthermore, an improved adaptive median filtering algorithm was presented. The experiment results show that the signature information carrier extracted by the improved adaptive median filter algorithm has more signature features, and increases the recognition accuracy and success rate.",
keywords = "Adaptive median filter algorithm, Binaryzation, Image preprocessing, Signature identification, Smooth filtering",
author = "Mei Wang and Lin, {Xiao Rong} and Liang Wang and Wen, {Miao Li} and Zan, {Hong Yang}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 International Conference on Computer Science and Applications, CSA 2015 ; Conference date: 20-11-2015 Through 22-11-2015",
year = "2017",
month = jan,
day = "6",
doi = "10.1109/CSA.2015.86",
language = "英语",
series = "2015 International Conference on Computer Science and Applications, CSA 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "55--59",
booktitle = "2015 International Conference on Computer Science and Applications, CSA 2015",
}