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    Computer Vision-Based QR Code Detection for Manipulation of a DC Motor in Semi-Controlled Environments
    (IEEE, 2023)
    Hernández Pérez, M. A.
    ;
    Pérez-Daniel, Karina Ruby
    ;
    Delgado Reyes, G.
    ;
    García Ramírez, P.
    ;
    Cane-González, C. J.
    The present research work carries out the design and implementation of a computer vision algorithm supported by image pre-processing techniques to improve the QR (Quick Response) code detection rate efficiency in a semi-controlled environment. The proposed algorithm is implemented in an embedded system using a Raspberry Pi model4B+ microcomputer to manipulate a DC motor that emulates the change in direction in a mobile robot. For greater precision and simplicity, the encoded data of the QR code are 1 and 0, which allow turning to the right or left, respectively, on the DC motor. To complement the embedded system, a Raspberry camera, and a control module (current regulator) for the DC motor are used. Finally, efficiency tests are carried out with the proposed algorithm, where the idea is to obtain a lower error factor compared to the tests carried out in classical algorithms that do not have image pre- processing stages. These tests are carried out in a semi-controlled environment, varying the luminosity and distance to detect the QR code. Once the objective is reached, the best light and distance conditions are proposed for detection, allowing the general system to be versatile and fast.
      7  2
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    A Computer Vision Approach to Terminus Movement Analysis of Viedma Glacier
    (2023)
    Moya-Albor, Ernesto  
    ;
    Schwartzman, Armin
    ;
    Brieva, Jorge  
    ;
    Pardo, Mauricio
    ;
    Ponce, Hiram  
    In this paper, an automatic segmentation approach of the Viedma glacier terminus is proposed. The method uses multi-spectral images from the Landsat-5 satellite to determine the area of the glacier through computer vision techniques. The area of the glacier is estimated, and a linear model is fitted, obtaining a correlation of 0.968 between the measured area and a fit linear regression model. On the other hand, a bio-inspired optical flow estimation approach is used to calculate and visualize the displacement of the glacier through time. In addition, an analysis is performed between the temperature variation in the Southern Cone and the decrease of the glacier in the function of time. A linear trend (r2=0.95) shows that the analyzed area of the glacier has decreased by about 1.9% annually in the observation season. It reveals an inverse relationship between the change in the size of the glacier and global warming, showing that if the same conditions remain, the glacier's zone analyzed in this work would be close to its disappearance in around 70 years, the time lapse in which a global temperature increase of 1.24 oC would be reached. © 2023 IEEE.
      14  1