@inproceedings{460ac736b0c5491ba717d6965a8a74ee,
title = "Text-independent writer identification using SIFT descriptor and contour-directional feature",
abstract = "This paper presents a method for text-independent writer identification using SIFT descriptor and contour-directional feature (CDF). The proposed method contains two stages. In the first stage, a codebook of local texture patterns is constructed by clustering a set of SIFT descriptors extracted from images. Using this codebook, the occurrence histograms are calculated to determine the similarities between different images. For each image, we obtain a candidate list of reference images. The next stage is to refine the candidate list using the contour-directional feature and SIFT descriptor. The proposed method is evaluated with two datasets: the ICFHR2012-Latin dataset and the ICDAR2013 dataset. Experimental results show that the proposed method outperforms the state-of-the-art algorithms and archives the best performance.",
keywords = "SIFT descriptor and contour-directional feature, Writer identification, codebook, text-independent",
author = "Xiong, \{Yu Jie\} and Ying Wen and Wang, \{Patrick S.P.\} and Yue Lu",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 13th International Conference on Document Analysis and Recognition, ICDAR 2015 ; Conference date: 23-08-2015 Through 26-08-2015",
year = "2015",
month = nov,
day = "20",
doi = "10.1109/ICDAR.2015.7333732",
language = "英语",
series = "Proceedings of the International Conference on Document Analysis and Recognition, ICDAR",
publisher = "IEEE Computer Society",
pages = "91--95",
booktitle = "13th IAPR International Conference on Document Analysis and Recognition, ICDAR 2015 - Conference Proceedings",
address = "美国",
}