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Moya-Albor, Ernesto
Modeling of the major temporal arcade using genetic algorithms and orthogonal polynomials
Authentication of medical images through a hybrid watermarking method based on Hermite-Jigsaw-SVD
2023
,
Soto-Alvarez, Jose Alfredo
,
Cruz-Aceves, Ivan
,
Hernandez-Aguirre, Arturo
,
Hernandez-Gonzalez, Martha Alicia
,
Lopez-Montero, Luis Miguel
,
Moya-Albor, Ernesto
,
Brieva, Jorge
,
Gomez-Coronel, Sandra L.
,
Pérez-Daniel, Karina Ruby
Nowadays eye diseases that are not treated in a timely manner can lead to blindness in the patient. Diabetic retinopathy and retinopathy of prematurity are a couple of conditions considered to be the main causes of blindness in both adults and children. The technique used to date to verify the status of the retina is a qualitative analysis by an ophthalmological expert of fundus images. However, this is entirely based on the experience acquired by the physician and being able to detect changes in the vascular structure of the retina is a great challenge which can be addressed through technology. This paper presents a novel method to carry out the numerical modeling of the major temporal arcade using orthogonal polynomials of Legendre, Chebyshev and Laguerre through a genetic algorithm that helps to determine the coefficients of the linear combination of each one. A set of twenty fundus images already outlined by an expert was used, which were processed by the algorithm, generating an adjustment curve on the set of pixels of the Major Temporal Arcade. The results obtained were compared with three existing methodologies in the literature by using two metrics, emerging the Legendre polynomials as the most suitable for modeling, as a consequence of the low values obtained in the metrics compared to the other methods. © 2023 SPIE.
2023
,
Gomez-Coronel, Sandra L.
,
Moya-Albor, Ernesto
,
Pérez-Daniel, Karina Ruby
,
Brieva, Jorge
,
Cruz-Aceves, Ivan
,
Hernandez-Aguirre, Arturo
,
Soto-Alvarez, Jose Alfredo
This work presents a watermarking algorithm applied to medical images by using the Steered Hermite Transform (SHT), the Singular Value Decomposition (SVD), and the Jigsaw transform (JS). The principal objective is to protect the patient's information using imperceptible watermarking and preserve its diagnosis. Thus, the watermark imperceptibility is achieved using the high-order Steered Hermite coefficients, whereas the SVD decomposition and the JS ensure the watermark against attacks. We use the medicine symbol Caduceus as a watermark. The metrics employed to evaluate the algorithm's performance are the Peak Signal-to-Noise Ratio (PSNR), the Mean Structural Similarity Index (MSSIM), and the Normalized Cross-Correlation (NCC). The evaluation metrics over the watermarked image show that it does not suffer quantitative and qualitative changes, and the extracted watermark was recovered successfully with high PSNR values. In addition, several watermark extraction tests were performed against geometric and common processing attacks. These tests show that the proposed algorithm is robust under critical conditions of attacks, for example, against nonlinear smoothing (median filter), high noise addition (Gaussian and Salt & Pepper noise), high compression rates (JPEG compression), rotation between 0 to 180 degree, and translations up to 100 pixels.