Super-resolution Image Created from a Sequence of Images with Application of Character Recognition
Author(s) -
Leandro Luiz de Almeida,
Maria Stela Veludo de Paiva,
Francisco Assis da Silva,
Almir Olivette Artero
Publication year - 2013
Publication title -
international journal of intelligent systems and applications
Language(s) - English
Resource type - Journals
eISSN - 2074-9058
pISSN - 2074-904X
DOI - 10.5815/ijisa.2014.01.02
Subject(s) - computer science , character (mathematics) , artificial intelligence , image (mathematics) , sequence (biology) , computer vision , resolution (logic) , pattern recognition (psychology) , character recognition , low resolution , high resolution , geology , mathematics , remote sensing , geometry , biology , genetics
Super-resolution techniques allow combine multiple images of the same scene to obtain an image with increased geometric and radiometric resolution, called super-resolution image. In this image are enhanced features allowing to recover important details and information. The objective of this work is to develop efficient algorithm, robust and automated fusion image frames to obtain a super-resolution image. Image registration is a fundamental step in combining several images that make up the scene. Our research is based on the determination and extraction of characteristics defined by the SIFT and RANSAC algorithms for automatic image registration. We use images containing characters and perform recognition of these characters to validate and show the effectiveness of our proposed method. The distinction of this work is the way to get the matching and merging of images because it occurs dynamically between elements common images that are stored in a dynamic matrix
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