Detection of Indonesian Vehicle Plate Location using Harris Corner Feature Detector Method
Fawwaz Ali Akbar, Hendra Maulana
Fawwaz Ali Akbar
Available Online December 2018.
- https://doi.org/10.2991/icst-18.2018.177How to use a DOI?
- Harris Corner, Morphological Filters, Plate Localization, Euclidean Distance
- Intelligent transportation systems are now starting to develop. One aspect of the intelligent transportation support system is how to recognize a vehicle. Vehicle plate recognition is an important function of this system. Plate detection systems have two problems, namely where the plate is located and how large the size is. Harris, Eigen and FAST methods have a high production value in detecting the number plate location. This is because the theoretical background is relatively focused on the angle. The Harris Corner detection system is often used because it can produce consistent values in rotating image and which has a lot of noise in an image. Morphological filters openings and closings can be seen as transformations with a structuring element which locally adapts its shape to the image structures, and therefore have lovely filtering capabilities. In this paper, we present the Indonesian plate localization based on text segmentation of unstructured standard plates with morphology filters openings and closings on pre-processing and feature detector Harris Corner method. Harris Corner method is used to detect corner points of the text, as well as using the Euclidean Distance algorithm to match features. The proposed result method produces an accuracy of 98.98%, a precision of 65.57% and a recall value of 73.55%. For further research, it needs to be compared with other methods to get the best results
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Fawwaz Ali Akbar AU - Hendra Maulana PY - 2018/12 DA - 2018/12 TI - Detection of Indonesian Vehicle Plate Location using Harris Corner Feature Detector Method BT - International Conference on Science and Technology (ICST 2018) PB - Atlantis Press SP - 877 EP - 881 SN - 2589-4943 UR - https://doi.org/10.2991/icst-18.2018.177 DO - https://doi.org/10.2991/icst-18.2018.177 ID - Akbar2018/12 ER -