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9 August 2018 Recognition of color changes in strawberry juice powders using self-organizing feature map
K. Przybył, J. Gawałek, L. Gierz, M. Łukomski, M. Zaborowicz, P. Boniecki
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Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 1080621 (2018) https://doi.org/10.1117/12.2503101
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China
Abstract
Self-Organizing Feature Map (SOFM), has been used for the qualitative identification of strawberry juice powders. The research was based on image recognition using powders obtained through an industrial spray-drying process. Results demonstrated that the color features were able to effectively distinguish the research material consisting of spray-dried powders of strawberry juice. The adequate model in terms of the lowest error value RMS (Root Mean Square) contained 46 neurons in the input layer and neurons in the output layer. The model is an effective tool for classifying wrong color changes in strawberry powders.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
K. Przybył, J. Gawałek, L. Gierz, M. Łukomski, M. Zaborowicz, and P. Boniecki "Recognition of color changes in strawberry juice powders using self-organizing feature map", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 1080621 (9 August 2018); https://doi.org/10.1117/12.2503101
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Cited by 4 scholarly publications.
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KEYWORDS
RGB color model

Image processing

Principal component analysis

Chromium

Image analysis

Manufacturing

Neural networks

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