Moya-Albor, Ernesto
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Moya-Albor, Ernesto
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Moya Albor, Ernesto
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emoya
Moya-Albor, E.
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55523223700
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J-1891-2019

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A perceptive watermarking approach applied to COVID-19 imaging data

2020 , Gomez-Coronel, Sandra L. , Moya-Albor, Ernesto , Brieva, Jorge , Ponce, Hiram

This work presents a watermarking algorithm applied to medical images of COVID-19 patients. The principal objective is to protect the information of the patient using an imperceptible watermarking and to preserve its diagnose. Our technique is based on a perceptive approach to insert the watermark by decomposing the medical image using the Hermite transform. We use as watermark two image logos, including text strings to demonstrate that the watermark can contain relevant information of the patient. Some metrics were applied to evaluate the performance of the algorithm. Finally, we present some results about robustness with some attacks applied to watermark images. © 2020 SPIE

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Optical Flow-Hermite and Fuzzy Q-Learning Based Robotic Navigation Approach

2021 , Moya-Albor, Ernesto , Brieva, Jorge , Ponce, Hiram , Gomez-Coronel, Sandra L.

The present paper presents a bio-inspired optical flow approach to autonomous robotics navigation. It uses a Fuzzy Q-Learning (FQL) method to take decisions in an unknown environment through a reinforcement signal. The proposed method was implemented in a virtual robotics system using the V-REP software and in communication con MATLAB. The preliminary results show that the robot was able to navigate successfully in unknown environments. © 2021 IEEE.

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Bio-inspired Optical Flow-based Autonomous Obstacle Avoidance Control

2019 , Moya-Albor, Ernesto , Gomez-Coronel, Sandra L. , Ponce, Hiram , Brieva, Jorge , Chávez Domínguez, Rodrigo , Guadarrama-Muñoz, Alexis E.

In this paper, we propose a new methodology for autonomous obstacle avoidance control using a bio-inspired optical flow estimation. The main difference with other methods is that we use an image model inspired by the human vision system to define the constraints in the optical flow formulation which includes a Hermite transform (HT) and a perceptive mask. We use a physical robot platform to test the control algorithm, where due to the structure of the chassis a forward, reverse and turn movements were defined. The robot has a RBG camera to capture images of the path and then calculate optical flow estimation. To define velocity and direction robot response we propose a fuzzy controller. Finally, we made some experiments to demonstrate the performance of control navigation, and how responds algorithm using HT and a perceptive mask. © 2019 IEEE.

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Motion magnification using the Hermite transform

2015 , Brieva, Jorge , Gomez-Coronel, Sandra L. , Moya-Albor, Ernesto , Escalante-Ramírez, Boris , Mora Esquivel, Juan I. , Ponce, Hiram

We present an Eulerian motion magnification technique with a spatial decomposition based on the Hermite Transform (HT). We compare our results to the approach presented in. We test our method in one sequence of the breathing of a newborn baby and on an MRI left ventricle sequence. Methods are compared using quantitative and qualitative metrics after the application of the motion magnification algorithm.

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Video motion magnification for monitoring of vital signals using a perceptual model

2017 , Brieva, Jorge , Moya-Albor, Ernesto , Gomez-Coronel, Sandra L. , Ponce, Hiram

In this paper we present an Eulerian motion magnification technique using a spatial decomposition based on the Steered Hermite Transform (SHT) which is inspired in the Human Vision System (HVS). We test our method in one sequence of the breathing of a newborn baby and on a video sequence that shows the heartbeat on the wrist. We estimate the heart pulse applying the Fourier transform on the magnified sequences. Our motion magnification approach is compared to the Laplacian and the Cartesian Hermite decomposition strategies by means of quantitative metrics. © 2017 SPIE.

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