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JSEG-based image segmentation in computer vision for agricultural mobile robot navigation
  • Universidade de São Paulo (USP)
  • Universidade Estadual Paulista (UNESP)
This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, 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 pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical 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 patterns in which reasonably accurate results were obtained.
Issue Date: 
Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA, p. 240-245.
Time Duration: 
  • Computer vision
  • Image processing
  • Image segmentation
  • Mobile robots
  • Artificial Neural Network
  • HSV space
  • Image processing technique
  • Mobile Robot Navigation
  • Navigation problem
  • Omnidirectional vision system
  • SIMULINK environment
  • Backpropagation algorithms
  • Digital image storage
  • Evolutionary algorithms
  • Imaging systems
  • Navigation
  • Neural networks
  • Robotics
  • Wireless networks
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Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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