Examinando por Autor "Mejía-Cabrera, Heber I."
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- PublicaciónSólo datosEvaluation of panchromatic and multispectral image fusion methods(Proceedings of SPIE - The International Society for Optical Engineering, 2020-08-24) Tuesta-Monteza, Victor; Pérez Vásquez, Yelsin; Mejía-Cabrera, Heber I.; G. Forero, ManuelEarth observation satellites provide multispectral images that are characterized by good spectral quality but low spatial quality. They also provide panchromatic images that, on the contrary, are characterized by good spatial quality but low spectral quality. Therefore, it is important to merge both images to obtain a single one that contains complementary information and can be used in land resource studies, surface geology, water management, forests, urban development, agriculture, and others. For this reason, it is important to evaluate the techniques used for the fusion of multispectral and panchromatic images: EIHS, Brovey and Averaging. Therefore, in this work these three techniques are evaluated, using the quantitative indices: spectral ERGAS and spatial ERGAS. In this way, the quality of the resulting fused images can be measured. Natural images were used to make the evaluation. The results show, on the one hand, that the best spectral quality is obtained with the Averaging algorithm, followed by the Brovey and, thirdly, by the EIHS. On the other hand, the best spatial quality was obtained with the EIHS algorithm, followed by the Brovey and then by the Averaging algorithm. It was also found that by averaging the values obtained in both evaluations that the best quality of fusion is obtained with the Averaging algorithm, followed by the Brovey and finally by the EIHS.
- PublicaciónSólo datosNew method for subject identification based on palm print(Proceedings of SPIE - The International Society for Optical Engineering, 2020-08-24) Mejía-Cabrera, Heber I.; Antón Chiclayo, Rafael; Flores, J. Nicolás; Tuesta-Monteza, Victor; G. Forero, ManuelNowadays, new security and protection systems for citizens are being developed, since criminals have found techniques to violate those already known, such as those based on fingerprints, facial recognition, iris and voice. Thus, using biometric data, new systems are being developed that are more secure, infallible and fast to identify each person, making it impossible to impersonate them, as has happened with other methods. Recently new identification methods have been proposed based on hand geometry and palmprint based on texture techniques for the identification of hand characteristics such as ridges, edges, points, and textures. Following this trend, this paper presents a method based on the detection of the palm print, acquired by contact, through the use of a scanner. For this purpose, the image is segmented to detect the silhouette of the hand and delimit the working area, achieving greater speed in identification. The images are then used as input to a convolutional neural network VGG 16 for learning and identification of subjects, achieving 100% accuracy.