Rizarta, Rusma (2019) Implementasi K-Nearest Neighbor dan Euclidean Distance untuk Aplikasi Pengenalan Citra Rambu Lalu Lintas. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
Traffic signs are one of the road equipment in particular forms containing symbols, letters, numbers, sentences used to give instruction, prohibitions, warnings and directions for road user to order the traffic. Traffic signs are often found by everyone, but many people don’t know the information in every traffic sign installed. This research makes an application to recognize the image of a traffic sign using the K-Nearest Neighbor and Euclidean Distance. User can input images and doing image processing start from preprocessing, segmentation, feature extreaction spatial moment, central moment and color statistics. The distance of the test image will be calculated with the training image and sort the smallest value to the largest and show the result based on the classification of K values chosen by the user. The researcher used three types of traffic signs that is four priority intersection warning, no parking and orders enter the designated route. This application uses 21 training images and 15 test images with the result of accuracy rate of K=3 is 100%, the value of K=5 is 86.6% and the value of K=7 is 86.6%. Keyword : K-Nearest Neighbor, Euclidean Distance, Traffic Sign, Images
| 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: | 01 Apr 2019 00:11 |
| Last Modified: | 01 Apr 2019 00:11 |
| URI: | http://eprints.uty.ac.id/id/eprint/2633 |
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