Recognition Number of The Vehicle Plate Using Otsu Method and K-Nearest Neighbour Classification
Abstract: The current topic
that is interesting as a solution of the impact of public service improvement
toward vehicle is License Plate Recognition (LPR), but it still needs to
develop the research of LPR method. Some of the previous researchs showed that
K-Nearest Neighbour (KNN) succeed in car license plate recognition. The
Objectives of this research was to determine the implementation and accuracy of
Otsu Method toward license plate recognition. The method of this research was
Otsu method to extract the characteristics and image of the plate into binary
image and KNN as recognition classification method of each character. The
development of the license plate recognition program by using Otsu method and
classification of KNN is following the steps of pattern recognition, such as
input and sensing, pre-processing, extraction feature Otsu method binary,
segmentation, KNN classification method and post-processing by calculating the
level of accuracy. The study showed that this program can recognize by 82% from
100 test plate with 93,75% of number recognition accuracy and 91,92% of letter
recognition accuracy.
Penulis: Maulidia Rahmah
Hidayah, Isa Akhlis, Endang Sugiharti
Kode Jurnal: jptinformatikadd170131