Suprapman, Eggy (2021) Klasifikasi Warna Mobil Berbasis Histogram Warna Menggunakan Multilayer Perception. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
ABSTRACT The color information of cars in particular is one of the essential elements in knowing a vehicle's identity. In writing this study, models or color - recognition methods of cars use multi-layered nerve cells (MLP). The introduction of color vehicles has an important role in intelligent transport systems (ITS) as analysis data such as criminal investigations, traffic surrvei and so on. Model design systems in research designed and implemented using python programming languages. The study consists of a two-stage process of processing digital image, extraction, feature and classification. Extraction marks using red, green, blue (RGB) and hue, saturation, value (HSV) while, the classification process USES the architecture of a multilayer replicas nerve network (MLP). Calcified into eight different colors of black, gray, silver, white, red, green, blue, and yellow. Testing in the process of color classification cars has an average value-size average 75%. Keywords: car colour, Image processing, Multilyer Perceptron, Histogram, RGB, HSV
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 27 Mar 2021 03:29 |
| Last Modified: | 27 Mar 2021 03:29 |
| URI: | http://eprints.uty.ac.id/id/eprint/7206 |
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