Introducción a la visión artificial: procesos y aplicaciones
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2022
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2022
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La visión artificial es una disciplina cuyo principal objetivo es procesar y analizar imágenes del mundo real, con la finalidad de que estas puedan ser entendidas y tratadas por un ordenador. El concepto de visión artificial surgió en la década de los sesenta del siglo pasado. Desde entonces ha ido ganando importancia y funcionalidades hasta convertirse hoy en día en uno de los mejores métodos de identificación de imágenes. La principal aplicación de la visión artificial es el reconocimiento de patrones y es utilizada en campos como la vigilancia y la seguridad, el reconocimiento facial y el funcionamiento de sistemas robóticos.
El elemento básico y principal de la visión artificial es el píxel, es decir, cada una de las partes que forman una imagen digital. En rasgos generales, la visión artificial consiste en una serie de operaciones matemáticas sobre los píxeles de la imagen, que varían dependiendo de lo que se quiera conseguir en cada momento. Estas operaciones reciben el nombre de filtros y se realizan a través de máscaras.
En este trabajo comenzaremos con una introducción teórica a la visión artificial, estudiando detalladamente los componentes y las etapas del proceso que se lleva a cabo. Posteriormente, pondremos este proceso en práctica con tres casos diferentes. El objetivo final será llevar a cabo un proceso de visión artificial desde el momento en el que se toma una fotografía hasta que el ordenador es capaz de procesar los elementos que forman esa imagen.
Computer vision is a discipline whose main objective is to process and analyze images of the real world so that they can be understood and processed by a computer. The concept of machine vision emerged in the 1960s. Since then, it has been gaining importance and functionality and has become one of the best methods of image identification. The main application of computer vision is pattern recognition and it is used in fields such as surveillance and security, facial recognition and the operation of robotic systems. The basic and main element of computer vision is the pixel, that is, each of the parts that make up a digital image. In general terms, computer vision consists of a series of mathematical operations on the pixels of the image, which vary depending on what is to be achieved at any given time. These operations are called filters and are performed through masks. In this work we will begin with a theoretical introduction to computer vision, studying in detail the components and stages of the process that is carried out. Subsequently, we will put this process into practice with three different case studies. The final objective will be to be able to create an artificial vision process from the moment a photograph is taken until the computer is able to understand the elements that form that image.
Computer vision is a discipline whose main objective is to process and analyze images of the real world so that they can be understood and processed by a computer. The concept of machine vision emerged in the 1960s. Since then, it has been gaining importance and functionality and has become one of the best methods of image identification. The main application of computer vision is pattern recognition and it is used in fields such as surveillance and security, facial recognition and the operation of robotic systems. The basic and main element of computer vision is the pixel, that is, each of the parts that make up a digital image. In general terms, computer vision consists of a series of mathematical operations on the pixels of the image, which vary depending on what is to be achieved at any given time. These operations are called filters and are performed through masks. In this work we will begin with a theoretical introduction to computer vision, studying in detail the components and stages of the process that is carried out. Subsequently, we will put this process into practice with three different case studies. The final objective will be to be able to create an artificial vision process from the moment a photograph is taken until the computer is able to understand the elements that form that image.