Writer-Identification_WLSR

Overview

• Dependences
• Line_Segmentation
• Feature_Extraction
• References
• Citation
• Contact

Codes of this repository are for papper entitled with "Semi-Supervised Feature Learning for Improving Writer Identification", which had been published on Information Sciences.

Dependences

• Matlab, Matconvnet, Opencv, NVIDIA GPU

• (Note that I have included my Matconvnet in this repo, so you do not need to download it again. I has changed some codes comparing with the original version. For example, one of the difference is in /matlab/+dagnn/@DagNN/initParams.m. If one layer has params, I will not initialize it again, especially for pretrained model.)

  You just need to uncomment and modify some lines in compile.m and run it in Matlab. Try it~ (The code does not support cudnn 6.0. You may just turn off the Enablecudnn or try cudnn5.1)

  If you fail in compilation, you may refer to http://www.vlfeat.org/matconvnet/install/

Line_Segmentation

At first, you segment the document to lines with statistical line segmentation. You can refer to guideline (https://github.com/KiM55/DLS-CNN/).

Feature_Extraction

Train

1. Make a dir called data by typing mkdir ./data.

2. Download ResNet-50 model pretrained on Imagenet. Put it in the data dir.

3. Add your original dataset path and extra dataset path into prepare_data.m and prepare_extra_data.m and run it. Make sure the code outputs the right image path.

4. Run train_id_net_res_market_wlsr.m (Single) or resnet52_2stream_wlsr_fc_identify_solely.m (2-Stream) for training the proposed method.

Test

Run test/feature_extraction.m to extract the features of images in the gallery and query set. They will store in a .mat file. Then you can use it to do evaluation.

Evaluation

Run evaluation/evaluation.m for evaluation.

References

• [1] 'Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro' by Zhedong Zheng et. al, paper, code
• [2] 'A Robust Off-line Writer Identification Method' by Shiming Chen et. al, paper, code

Citation

If this work is helpful for you, please cite my paper.

@article{Chen2019Semi,  
  title={Semi-Supervised Feature Learning for Improving Writer Identification},    
  author={Chen, Shiming and Wang, Yisong and Lin, Chin-Teng Lin and Ding, Weiping and Cao, Zehong},    
  journal={Information Sciences}, 
  volume={482},
  pages={156-170},
  year={2019}    
}

Contact

If you run into any problems with these codes, please submit a bug report on the Github site of the project. For another inquries please contact with me: gchenshiming@gmail.com or g_shmchen@163.com