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      Recognition System Using the Local Binary Pattern Method and Support Vector Machine to Detect Outdoor Parking Spaces

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      ScienceOpen Preprints
      ScienceOpen
      Local Binary Pattern Rotation Invariant Uniform, Support Vector Machine, Gaussian Blur
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            Abstract

            The increase in the volume of vehicles causes the parking quota in a parking lot to decrease and the density in the parking slots makes it difficult for visitors to find empty parking slots, which will waste time in searching for parking spaces. Researchers use Gamma Correction, Gaussian Blur, Local Binary Pattern . methods Rotation Invariant Uniform and Support Vector Machine with Gaussian Blur parameter settings using no kernel, Gamma Correction using gamma = 15, Local Binary Pattern Rotation Invariant Uniform P=8 and R=1 and Support Vector Machine kernel RBF getting an accuracy value of 99.52% better than journals [3] by method �������� 98.90% accuracy and �������������� with 82.78% accuracy.

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            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            27 February 2022
            Affiliations
            [1 ] Telkom University
            Author notes
            Article
            10.14293/S2199-1006.1.SOR-.PPORCAZ.v1
            93dc3c82-edae-40e6-b045-6fddc1d57ebf

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .


            All data generated or analysed during this study are included in this published article (and its supplementary information files).
            Computer science,Engineering
            Local Binary Pattern Rotation Invariant Uniform, Support Vector Machine, Gaussian Blur

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