no code implementations • 8 Sep 2023 • Rayson Laroca, Luiz A. Zanlorensi, Valter Estevam, Rodrigo Minetto, David Menotti
License Plate Recognition (LPR) plays a critical role in various applications, such as toll collection, parking management, and traffic law enforcement.
no code implementations • 15 Apr 2022 • Diego Rafael Lucio, Luiz A. Zanlorensi, Yandre Maldonado e Gomes da Costa, David Menotti
Accurate extraction of the Region of Interest is critical for successful ocular region-based biometrics.
no code implementations • 24 Nov 2020 • Luiz A. Zanlorensi, Rayson Laroca, Diego R. Lucio, Lucas R. Santos, Alceu S. Britto Jr., David Menotti
Thus, the use of datasets containing many subjects is essential to assess biometric systems' capacity to extract discriminating information from the periocular region.
Ranked #1 on Image Classification on Imbalanced CUB-200-2011
no code implementations • 21 Sep 2020 • Rayson Laroca, Alessandra B. Araujo, Luiz A. Zanlorensi, Eduardo C. de Almeida, David Menotti
Existing approaches for image-based Automatic Meter Reading (AMR) have been evaluated on images captured in well-controlled scenarios.
Ranked #1 on Meter Reading on UFPR-AMR Dataset
Image-based Automatic Meter Reading Optical Character Recognition (OCR)
no code implementations • 10 Feb 2020 • Luiz A. Zanlorensi, Hugo Proença, David Menotti
Ocular biometric systems working in unconstrained environments usually face the problem of small within-class compactness caused by the multiple factors that jointly degrade the quality of the obtained data.
no code implementations • 21 Nov 2019 • Luiz A. Zanlorensi, Diego R. Lucio, Alceu S. Britto Jr., Hugo Proença, David Menotti
One of the major challenges in ocular biometrics is the cross-spectral scenario, i. e., how to match images acquired in different wavelengths (typically visible (VIS) against near-infrared (NIR)).
no code implementations • 21 Nov 2019 • Luiz A. Zanlorensi, Rayson Laroca, Eduardo Luz, Alceu S. Britto Jr., Luiz S. Oliveira, David Menotti
The use of the iris and periocular region as biometric traits has been extensively investigated, mainly due to the singularity of the iris features and the use of the periocular region when the image resolution is not sufficient to extract iris information.
1 code implementation • 4 Sep 2019 • Rayson Laroca, Luiz A. Zanlorensi, Gabriel R. Gonçalves, Eduardo Todt, William Robson Schwartz, David Menotti
This paper presents an efficient and layout-independent Automatic License Plate Recognition (ALPR) system based on the state-of-the-art YOLO object detector that contains a unified approach for license plate (LP) detection and layout classification to improve the recognition results using post-processing rules.
Ranked #1 on License Plate Recognition on Caltech Cars
no code implementations • 31 Jul 2019 • Diego R. Lucio, Rayson Laroca, Luiz A. Zanlorensi, Gladston Moreira, David Menotti
In this work, we propose to detect the iris and periocular regions simultaneously using coarse annotations and two well-known object detectors: YOLOv2 and Faster R-CNN.
no code implementations • 29 Aug 2018 • Luiz A. Zanlorensi, Eduardo Luz, Rayson Laroca, Alceu S. Britto Jr., Luiz S. Oliveira, David Menotti
The use of iris as a biometric trait is widely used because of its high level of distinction and uniqueness.
no code implementations • 3 Mar 2018 • Evair Severo, Rayson Laroca, Cides S. Bezerra, Luiz A. Zanlorensi, Daniel Weingaertner, Gladston Moreira, David Menotti
The iris is considered as the biometric trait with the highest unique probability.
2 code implementations • 26 Feb 2018 • Rayson Laroca, Evair Severo, Luiz A. Zanlorensi, Luiz S. Oliveira, Gabriel Resende Gonçalves, William Robson Schwartz, David Menotti
First, in the SSIG dataset, composed of 2, 000 frames from 101 vehicle videos, our system achieved a recognition rate of 93. 53% and 47 Frames Per Second (FPS), performing better than both Sighthound and OpenALPR commercial systems (89. 80% and 93. 03%, respectively) and considerably outperforming previous results (81. 80%).
Ranked #2 on License Plate Recognition on SSIG-SegPlate