M
Moises Diaz-Cabrera
Researcher at University of Las Palmas de Gran Canaria
Publications - 19
Citations - 616
Moises Diaz-Cabrera is an academic researcher from University of Las Palmas de Gran Canaria. The author has contributed to research in topics: Signature (logic) & Signature recognition. The author has an hindex of 12, co-authored 19 publications receiving 546 citations.
Papers
More filters
Journal ArticleDOI
Static Signature Synthesis: A Neuromotor Inspired Approach for Biometrics
TL;DR: A new method for generating synthetic handwritten signature images for biometric applications that imitate the mechanism of motor equivalence which divides human handwriting into two steps: the working out of an effector independent action plan and its execution via the corresponding neuromuscular path.
Journal ArticleDOI
On-line signature recognition through the combination of real dynamic data and synthetically generated static data
Javier Galbally,Moises Diaz-Cabrera,Miguel Ferrer,Marta Gomez-Barrero,Aythami Morales,Julian Fierrez +5 more
TL;DR: A novel approach is explored and evaluated that takes advantage of the performance boost that can be reached through the fusion of on-line and off-line signatures and of their potential combination both in the random and skilled impostors scenarios.
Proceedings ArticleDOI
Suspended traffic lights detection and distance estimation using color features
TL;DR: A novel technique to detect suspended traffic lights, based on colors and features such as black area of traffic lights or area of lighting lamps is presented, which aims at slowing down and stopping in the correct position, in case of red light.
Journal ArticleDOI
Robust real-time traffic light detection and distance estimation using a single camera
TL;DR: The paper shows that the developed advanced driver assistance system is able to detect the traffic lights with 99.4% of accuracy in the range of 10-115m.
Proceedings ArticleDOI
Synthetic off-line signature image generation
TL;DR: The range of the static signature generator has been established matching the performance obtained with the synthetic databases and those obtained with two public databases, and an ink deposition model based on a ballpoint is developed for realistic static signature image generation.