Increasing the accuracy of object boundaries detection and the quality of machine-vision system data in terms of machine processing by a collaborative complex

Evgenii Semenishchev; Igor Shraifel; Sergey Makov; Egor Surkov; Aleksandr Zelensky; Viacheslav Voronin

doi:10.1117/12.2666764

14 June 2023 Increasing the accuracy of object boundaries detection and the quality of machine-vision system data in terms of machine processing by a collaborative complex

Evgenii Semenishchev, Igor Shraifel, Sergey Makov, Egor Surkov, Aleksandr Zelensky, Viacheslav Voronin

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Proceedings Volume 12547, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII; 1254714 (2023) https://doi.org/10.1117/12.2666764
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

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Abstract

To article proposes an approach to improve the quality of data used in various processes based on machine vision systems. The paper proposes a combined approach to applying the method of multi-criteria processing based on the use of a combined criterion in order to implement an edge detector, smoothing and separation areas of the background / object in the image. The application of the method allows eliminating the noise caused by external factors (such as dust and water suspension on the lens or space). The generated data make it possible to form an adaptive criterion for changing the correction parameters for a non-linear change in color balance in areas of increased detail or selected masks of changes blocks. The proposed algorithms make it possible to increase the visibility of small elements, reduce the noise component, while maintaining the boundaries of objects, increase the accuracy of selecting the boundaries of objects and the visual quality of data. As test data used to evaluate the effectiveness, nature data and expert evaluation results for test images obtained by a machine vision system with a sensor with a resolution of 1024x768 (8-bit, color image, visible range) are used. Images of simple shapes are used as analyzed objects.

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Evgenii Semenishchev, Igor Shraifel, Sergey Makov, Egor Surkov, Aleksandr Zelensky, and Viacheslav Voronin "Increasing the accuracy of object boundaries detection and the quality of machine-vision system data in terms of machine processing by a collaborative complex", Proc. SPIE 12547, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII, 1254714 (14 June 2023); https://doi.org/10.1117/12.2666764

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