Banknote Authentication
Donated on 4/15/2013
Data were extracted from images that were taken for the evaluation of an authentication procedure for banknotes.
Dataset Characteristics
Multivariate
Subject Area
Computer Science
Associated Tasks
Classification
Feature Type
Real
# Instances
1372
# Features
4
Dataset Information
Additional Information
Data were extracted from images that were taken from genuine and forged banknote-like specimens. For digitization, an industrial camera usually used for print inspection was used. The final images have 400x 400 pixels. Due to the object lens and distance to the investigated object gray-scale pictures with a resolution of about 660 dpi were gained. Wavelet Transform tool were used to extract features from images.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| variance | Feature | Continuous | variance of Wavelet Transformed image | no | |
| skewness | Feature | Continuous | skewness of Wavelet Transformed image | no | |
| curtosis | Feature | Continuous | curtosis of Wavelet Transformed image | no | |
| entropy | Feature | Continuous | entropy of image | no | |
| class | Target | Integer | no |
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Additional Variable Information
1. variance of Wavelet Transformed image (continuous) 2. skewness of Wavelet Transformed image (continuous) 3. curtosis of Wavelet Transformed image (continuous) 4. entropy of image (continuous) 5. class (integer)
Dataset Files
| File | Size |
|---|---|
| data_banknote_authentication.txt | 45.3 KB |
Papers Citing this Dataset
Sort by Year, desc
By Kathrin Grosse, Michael Smith, Michael Backes. 2018
Published in
By Yongli Sang, Xin Dang, Yichuan Zhao. 2018
Published in Journal of Statistical Planning and Inference.
By Hiroaki Sasaki, Takafumi Kanamori, Aapo Hyvarinen, Gang Niu, Masashi Sugiyama. 2017
Published in J. Mach. Learn. Res..
By Zeeshan Malik, Amir Hussain, Q. Wu. 2016
Published in Neurocomputing.
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset banknote_authentication = fetch_ucirepo(id=267) # data (as pandas dataframes) X = banknote_authentication.data.features y = banknote_authentication.data.targets # metadata print(banknote_authentication.metadata) # variable information print(banknote_authentication.variables)
Lohweg, V. (2012). Banknote Authentication [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C55P57.
Creators
Volker Lohweg
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.