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Construction of small sets of reference images for feature descriptors fitting and their use in the multiclassification of parts in industry

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Abstract

Industry 4.0 requires flexible and fast solutions to automatically identify and handle different parts during the production process. For such a multiclassification (MCC) task, usually feature detectors or machine learning approaches are used. However, increasing product variety and consequently rising number of classes impel the expansion of data set sizes, a mandatory procedure for accurate object identification. The acquisition of a sufficiently large number of sample images is a costly and time-consuming issue. This work presents an iterative reference data set creation method of small size image data sets for feature descriptor-based MCC. The novel method compares the shape of an object in a candidate image with the shapes from a growing reference image set consisting of all previously accepted candidates. An image is assigned to or rejected from the reference data set depending on the found shape similarity. Rejected images form a grid search set that is later used to optimize the feature descriptors’ hyperparameters and enable the addition of new classes. The benefits of this method are the small number of images to be acquired for MCC, the possibility of adding new parts without re-training, the little overhead for new applications, and its compatibility with most commonly used feature descriptors. When compared with a small control data set provided by an inexperienced user with an accuracy of 49% for a five classes MCC, the reference data set built by the novel method gains 20% on the accuracy (69%, 21 images in total) and can be performed by the same inexperienced user.

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Funding

This study was financed in part by the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brasil (CAPES) - Finance Code 001 and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2023 Internet of Production – 390621612.

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Authors and Affiliations

  1. Federal University of Santa Catarina, Labmetro, Florianopolis, Brazil

    Herberth Birck Fröhlich & Armando Albertazzi Goncalves Jr.

  2. Laboratory for Machine Tools and Production Engineering - WZL, Aachen, Germany

    Natalia Grozmani, Dominik Wolfschläger & Robert H. Schmitt

Authors
  1. Herberth Birck Fröhlich
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  2. Natalia Grozmani
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  3. Dominik Wolfschläger
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  4. Armando Albertazzi Goncalves Jr.
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  5. Robert H. Schmitt
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Correspondence to Herberth Birck Fröhlich.

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Fröhlich, H.B., Grozmani, N., Wolfschläger, D. et al. Construction of small sets of reference images for feature descriptors fitting and their use in the multiclassification of parts in industry. Int J Adv Manuf Technol 108, 105–116 (2020). https://doi.org/10.1007/s00170-020-05253-6

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  • DOI: https://doi.org/10.1007/s00170-020-05253-6

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