Warning: This repository is outdated and it won't be maintained in future. Please refer to the repository https://github.com/boortel/AE-Reconstruction-And-Feature-Based-AD and to the ModelClassificationSIFT.py module for its direct Python reimplemantation. SURF based feature extractor will be added later.

SIFT-and-SURF-based-AD

Implementation of the paper SIFT and SURF based feature extraction for the anomaly detection

Download the dataset at: https://www.kaggle.com/imonbilk/industry-biscuit-cookie-dataset

EDIT: New version of the dataset with the cropped images and simplified annotations is available as Version 2. Please use the script DatasetFolder.py attached to the dataset when using the updated version and the script in this repository for Version 1.

Download the Matlab SVDD code from: https://www.mathworks.com/matlabcentral/fileexchange/69296-support-vector-data-description-svdd and copy the Svdd folder to your working directory.

Please cite the following authors in your work:

@inproceedings{BUT177722,
  author="Šimon {Bilík} and Karel {Horák}",
  title="SIFT and SURF based feature extraction for the anomaly detection",
  address="Brno University of Technology, Faculty of Electrical Engineering",
  booktitle="Proceedings I of the 28 th Conference STUDENT EEICT 2022",
  chapter="177722",
  howpublished="online",
  institution="Brno University of Technology, Faculty of Electrical Engineering",
  year="2022",
  month="april",
  pages="459--464",
  publisher="Brno University of Technology, Faculty of Electrical Engineering"
}

@misc{Qiu2022,
  author = {Kepeng Qiu},
  journal = {GitHub},
  title = {Support Vector Data Description (SVDD)},
  subtitle = {MATLAB code for abnormal detection using Support Vector Data Description (SVDD)},
  year = {2022},
  medium = {online},
  accessed = {2022-10-11},
  URL = {https://github.com/iqiukp/SVDD-MATLAB/releases/tag/v2.1.5},
}