Ingeniería en Sistemas, Electrónica e Industrial

URI permanente para esta comunidadhttp://repositorio.uta.edu.ec/handle/123456789/1

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2021 - 20232

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Tipo de acceso: Acceso abiertoTema: search.filters.subject.BINARIZACIÓN

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  • Miniatura
    Item type:Ítem,
    Sistema automático de registro de automóviles y manejo del historial de trabajos para la microempresa “Tecnicars David” utilizando Machine Learning
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Telecomunicaciones, 2023-09)
    Pérez Valencia, Carlos Alfonso
    ;
    Benalcázar Palacios, Freddy Geovanny
    The present research project proposes the implementation of an automatic registration system to optimize and streamline administrative processes in "Tecnicars David" Workshop, demonstrating the relevance of this work in the field of automotive service automation. The importance of the project lies in the implementation of fuzzy logic as a character recognition technique and the integration of different technologies and tools to achieve a complete and efficient system. The system utilizes fuzzy logic as a character recognition technique and machine learning for managing the history of jobs performed. The fuzzy logic technique demonstrates the system's ability to handle situations of uncertainty or blurriness in plate images, allowing for the reconstruction and completion of characters in case they are illegible or blurry. The system leverages various open-source technologies and tools. It uses the Python programming language, the OpenCV library for motion and edge detection, and fuzzy logic for data extraction from plate images. The system interface features a dashboard built on Node-Red, providing an intuitive and efficient visualization for vehicle management in the workshop. This graphical interface is tailored to the specific requirements of the workshop offering a user-friendly experience and comprehensive registration of necessary information. The automatic registration system has undergone rigorous testing demonstrating efficient and reliable operation. The system's reliability has been evaluated, achieving a high percentage of vehicle plate recognition using fuzzy logic with 90.90% effectiveness. The system has also achieved a low error rate, indicating satisfactory precision in vehicle detection and registration This has resulted in improved efficiency and enhanced vehicle management processes at "Tecnicars David" workshop.
  • Miniatura
    Item type:Ítem,
    Implementación de un sistema inteligente para la identificación vehicular
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021)
    Cáceres Mayorga, Paúl Alejandro
    ;
    Reinoso Astudillo, Cristina Isabel
    The main objective of this research work was to implement an intelligent system capable of classifying vehicle and automotive license plates, as well as self-correcting recognition errors, for which it was based on the design of an algorithm capable of detecting and classifying vehicles, implementing artificial intelligence. Once the process to be followed was identified, a source code was implemented for the detection of the types of license plates using the convolutional neural network WPOD in which the data of the edge, width and height of the plate were specified so that it only provides the photo of license plate. For the binarization process used in the research, the Otsu algorithm was used, which converts the images into the gray, blur, binary and dilation scales, applying filters that can obtain the location segments of the letters and numbers. Finally, an effective system was obtained, with acceptable detection capacity, since design parameters of the architecture of each type of red were established, which achieved a satisfactory solution to the problem of identification, classification and validation of the characters of Ecuadorian license plates.