JIHAD EL SANA

Senior Academic

Word spotting using convolutional siamese network

Berat Kurar Barakat, Reem Alasam, Jihad El-Sana

We present a method for word spotting using convolutional siamese network. A convolutional siamese network employs two identical convolutional network to rank similarity between two input word images. Once the network is trained, it can then be used to spot not just words with varying writing styles and backgrounds but also to spot out of vocabulary words that are not in the training set. Experiments on the historical Arabic manuscript dataset VML, and on the George Washington dataset shows comparable results with the state of the art.

Publication language English
Pages 229-234
Publication status Published - 22.06.2018

Keywords

Historical document image analysis
convolutional siamese network
deep learning
word spotting

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Signal Processing
Access to Document
10.1109/DAS.2018.67
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Link to publication in Scopus