Abstract
The article proposes new algorithms for extracting recognizable features of one-dimensional vectors obtained from digital images and comparing them. Vectors store one byte, i.e. values in the range 0 ÷ 255 taken from a grayscale image. The features of hills located in the intervals of the local minima of the vector were taken as identification features. In particular, the area of the selected hill, its width, the coordinate of the local maximum located on this hill, etc. are taken.
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Tuktasinov, M. (2023). Algorithms for Selecting and Comparing Features of Digital Image Vectors Based on the Analysis of Local Extrema. In: Zaynidinov, H., Singh, M., Tiwary, U.S., Singh, D. (eds) Intelligent Human Computer Interaction. IHCI 2022. Lecture Notes in Computer Science, vol 13741. Springer, Cham. https://doi.org/10.1007/978-3-031-27199-1_55
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DOI: https://doi.org/10.1007/978-3-031-27199-1_55
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