GENERAL INFORMATION
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1. Title of Dataset: 
Burr detection and classification using RUSTICO and image processing


2. Authorship: 

Name: Riego Del Castillo, Virginia
Institution: Universidad de León 
Email: vriec@unileon.es
ORCID: https://orcid.org/0000-0003-3389-0786

Name: Sánchez González, Lidia
Institution: Universidad de León 
Email: gerlsg@unileon.es
ORCID: https://orcid.org/0000-0002-0760-1170


DESCRIPTION
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1. Dataset language: 
English 

2. Abstract:

[ES] El sistema desarrollado detecta y clasifica rebabas en piezas de 
mecanizado cuyas imágenes son tomadas por una cámara de microscopio 
(captura las imágenes RGB con una resolución de 2592 × 1994 píxeles) 
conectada a un boroscopio rígido industrial para analizar la forma de sus bordes 
a escala microscópica. Las imágenes adquiridas se procesan aplicando un método de 
delineación de estructuras de interés denominado RUSTICO (RobUST Inhibition-augmented Curvilinear Operator). 
Las imágenes son etiquetadas por expertos según los criterios propuestos las tres categorías consideradas: 
si no presenta imperfecciones (rebaba tipo cuchillo, K) que sería la situación ideal, si presenta pequeñas 
astillas (rebaba tipo sierra, S), que podría aceptarse en función del uso de la pieza mecanizada o si ha sufrido 
una gran deformación (rebaba-rotura, B) que produce una pieza inutilizable.
 
[EN] The developed system detects and classifies burrs in workpieces 
whose images are taken by a microscope camera (captures the RGB images with a resolution of 2592 × 1994 pixels) 
connected to an industrial rigid boroscope so as to analyze their edge shape on a microscopic scale. 
The acquired images are processed by applying a method for delineation of structures of interest called RUSTICO 
(RobUST Inhibition-augmented Curvilinear Operator). Images are labeled by experts according to the criteria proposed 
the three considered categories: if there is no imperfections (knife-type burr, K) that would be the ideal situation, 
if it presents small splinters (saw-type burr, S), which could be accepted depending on the use of the machined piece or 
if it has suffered a large deformation (burr-breakage, B) that produces an unusable piece.

3. Keywords: 
Piezas mecanizadas, Rebabas en fabricación, Clasificación de rebabas, RUSTICO, Milling machined parts, Burrs in workpiece, Burr classification

4. Date of data collection:
 2019

5. Publication Date:
 2021-07-30

6. Grant information:  

PID2019-108277GB-C21

7. Geographical location/s of data collection:



ACCESS INFORMATION
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1. Dataset Creative Commons License:
CC BY-NC-ND 4.0

2. Dataset DOI: 

10.18002/10612/15781


3. Related publication:

Riego, V., Sánchez-González, L., Fernández-Robles, L., Gutiérrez-Fernández, A., & Strisciuglio, N. (2021). Burr detection and classification using RUSTICO and image processing[Formula presented]. Journal of Computational Science, 56. https://doi.org/10.1016/J.JOCS.2021.101485


METHODOLOGICAL INFORMATION
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1. Description of methods used for collection-generation of data: 


FILE OVERVIEW
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1. File List: 
 https://ss3.scayle.es:443/burr/info_category.csv
 https://ss3.scayle.es:443/burr/rustico.zip
 https://ss3.scayle.es:443/burr/original.zip

 
2. Relationship between files:

3. File format:
CSV, ZIP


DATA-SPECIFIC INFORMATION
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