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27 November 2023 Algorithm for detection and classification of small objects on a complicated background to automated robotic complex
Evgenii Semenishchev, Salavat Urunov, Yuriy Ilyukhin, Aleksey Siryakov, Viacheslav Voronin
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Proceedings Volume 12769, Optical Metrology and Inspection for Industrial Applications X; 127691N (2023) https://doi.org/10.1117/12.2691386
Event: SPIE/COS Photonics Asia, 2023, Beijing, China
Abstract
The article proposes an approach to the determination of small-form objects against a complex background. The proposed approach uses a parallel data processing algorithm that includes the following main modules: a multi-criteria image filtering block built on an objective function that minimizes the weighted average sum of the average square of the first order finite difference, as well as the average square of the distance difference between the input implementation and the generated data; parallel separation of objects by analyzing local features, statistical analysis of histogram changes, building a mask of object detailing and frequency analysis; the formation of a feature mask and the search for similarity elements by analyzing the generated features. On the test data set, an example of determining small-sized objects on a complex background with their subsequent classification into class objects is presented. The data were obtained by a machine vision system installed on a robotic complex. Data on the required parameters of the formed machine vision systems are given, recommendations on the required parameters of the algorithms are presented.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Evgenii Semenishchev, Salavat Urunov, Yuriy Ilyukhin, Aleksey Siryakov, and Viacheslav Voronin "Algorithm for detection and classification of small objects on a complicated background to automated robotic complex", Proc. SPIE 12769, Optical Metrology and Inspection for Industrial Applications X, 127691N (27 November 2023); https://doi.org/10.1117/12.2691386
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KEYWORDS
Object detection
Detection and tracking algorithms
Statistical analysis
Machine vision
Data processing
Scene classification
Industry
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