Pajkovski, Darko and Jolevski, Ilija and Rendevski, Nikola (2024) Automatic private parking system using license plate recognition and car make and model recognition. In: ETAI2024, 21-23 Sep 2024, Struga, North Macedonia.
![[thumbnail of ETAI_2024_paper_15.pdf]](https://eprints.uklo.edu.mk/style/images/fileicons/text.png) |
Text
ETAI_2024_paper_15.pdf Download (457kB) |
Abstract
In this paper we purpose an automatic gate
system for parking space entry with authenticity confirmation
from 2 individual modules, car make and model and license
plate detection. The vehicle detection sensor identifies when
cars come to a halt in front of the gate, prompting the camera
to snap images of them. The approach used to segment the
images in license plate detection is connected component
analysis. Connected regions indicate that all pixels sharing a
connection are part of the same object or entity within the
image. The algorithm for detecting car make and model
utilizes feature extraction methods such as the Difference of
Gaussians (DoG) detector and the Scale Invariant Feature
Transform (SIFT) descriptor. These techniques help identify
distinctive visual features of cars, enabling accurate
recognition and classification. The Euclidean distance measure
is employed to find the most suitable match between a query
image and those stored in the database. This comparison aids
in determining the car's make and model by assessing the
similarity of visual features extracted from both the query and
database images. In the final stage, matching algorithms are
applied to decide whether the output of the LPR and make and
model detection does not conflict with the details stored in
database. Access to a parking lot is granted only when specific
conditions are met.
| Item Type: | Conference or Workshop Item (Speech) |
|---|---|
| Subjects: | Scientific Fields (Frascati) > Natural sciences > Computer and information sciences Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering |
| Divisions: | Faculty of Information and Communication Technologies |
| Depositing User: | MSc Darko Pajkovski |
| Date Deposited: | 01 Nov 2024 15:19 |
| Last Modified: | 01 Nov 2024 15:19 |
| URI: | https://eprints.uklo.edu.mk/id/eprint/10423 |
Actions (login required)
 |
View Item |