Next Article in Journal
Numerical Investigation of Blast Performance of Plate-Reinforced Moment-Resisting Connection Using Large Concrete Filled Tubular Section
Next Article in Special Issue
Vision-Based Sorting Systems for Transparent Plastic Granulate
Previous Article in Journal
Is It Possible to Restore a Heavily Polluted, Shallow, Urban Lake?
Previous Article in Special Issue
Semantic Component Association within Object Classes Based on Convex Polyhedrons
Open AccessArticle

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 0.031 with respect to the best descriptor alone. View Full-Text
Keywords: computer vision; feature descriptor; histogram; feature subset selection; industrial objects computer vision; feature descriptor; histogram; feature subset selection; industrial objects
Show Figures

Figure 1

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 Style

Merino, 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.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop