Histogram-Based Descriptor Subset Selection for Visual Recognition of Industrial Parts
1
TECNALIA, Basque Research and Technology Alliance (BRTA), Paseo Mikeletegi 7, 20009 Donostia-San Sebastian, Spain
2
Department of Computer Science and Artificial Intelligence, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(11), 3701; https://doi.org/10.3390/app10113701
Received: 1 April 2020 / Revised: 22 May 2020 / Accepted: 25 May 2020 / Published: 27 May 2020
(This article belongs to the Special Issue Applications of Computer Vision in Automation and Robotics)
This article deals with the 2D image-based recognition of industrial parts. Methods based on histograms are well known and widely used, but it is hard to find the best combination of histograms, most distinctive for instance, for each situation and without a high user expertise. We proposed a descriptor subset selection technique that automatically selects the most appropriate descriptor combination, and that outperforms approach involving single descriptors. We have considered both backward and forward mechanisms. Furthermore, to recognize the industrial parts a supervised classification is used with the global descriptors as predictors. Several class approaches are compared. Given our application, the best results are obtained with the Support Vector Machine with a combination of descriptors increasing the F1 by with respect to the best descriptor alone.
View Full-Text
Keywords:
computer vision; feature descriptor; histogram; feature subset selection; industrial objects
▼
Show Figures
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Merino, I.; Azpiazu, J.; Remazeilles, A.; Sierra, B. Histogram-Based Descriptor Subset Selection for Visual Recognition of Industrial Parts. Appl. Sci. 2020, 10, 3701. https://doi.org/10.3390/app10113701
AMA Style
Merino I, Azpiazu J, Remazeilles A, Sierra B. Histogram-Based Descriptor Subset Selection for Visual Recognition of Industrial Parts. Applied Sciences. 2020; 10(11):3701. https://doi.org/10.3390/app10113701
Chicago/Turabian StyleMerino, Ibon; Azpiazu, Jon; Remazeilles, Anthony; Sierra, Basilio. 2020. "Histogram-Based Descriptor Subset Selection for Visual Recognition of Industrial Parts" Appl. Sci. 10, no. 11: 3701. https://doi.org/10.3390/app10113701
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
Search more from Scilit