ANN statistical image recognition method for computer vision in agricultural mobile robot navigation
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Data
2010-11-29
Orientador
Coorientador
Pós-graduação
Curso de graduação
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Acesso aberto
Resumo
The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.
Descrição
Palavras-chave
Artificial neural networks, Computer vision, Image recognition and processing, Mobile robots, Application area, Artificial Neural Network, Computational platforms, HSV space, Mobile Robot Navigation, Multi layer perceptron, Navigation problem, Omnidirectional vision system, Recognition methods, Segmentation techniques, Segmented images, SIMULINK environment, Statistical images, Backpropagation algorithms, Image recognition, Image segmentation, Mechatronics, Navigation, Neural networks, Wireless networks
Idioma
Inglês
Como citar
2010 IEEE International Conference on Mechatronics and Automation, ICMA 2010, p. 1771-1776.
