@inproceedings{7b4975c85a8349b5813558b965f88272,
title = "Text extraction from mail images with complex background",
abstract = "A novel method is proposed for text extraction from mail images with complex background. Firstly, wavelet transform and Laplacian operator are applied to generate the features of regions which are obtained by dividing input image with sliding window. Then, support vector machine (SVM) is utilized to classify these regions into texts and non-texts according to the features. Bootstrap strategy is used to build the training database. Finally, connected components analysis (CCA) is employed to merge text regions into text candidates which can be processed by following steps to get the delivery address. Experimental results involving 534 mail images show the effectiveness and robustness of the proposed method, and comparison results with other methods demonstrate the advantages of the selected features.",
keywords = "Mail images, SVM, Text extraction, Wavelet transform",
author = "Qingqing Wang and Xiao Tu and Shujing Lu and Yue Lu",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 14th International Forum of Digital TV and Wireless Multimedia Communication, IFTC 2017 ; Conference date: 08-11-2017 Through 09-11-2017",
year = "2018",
doi = "10.1007/978-981-10-8108-8\_1",
language = "英语",
isbn = "9789811081071",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "3--11",
editor = "Xiaokang Yang and Guangtao Zhai and Jun Zhou",
booktitle = "Digital TV and Wireless Multimedia Communication - 14th International Forum, IFTC 2017, Revised Selected Papers",
address = "德国",
}