Title :
Cognitive-Merged Statistical Pattern Recognition Method for Image Processing in Mobile Robot Navigation
Author :
Lulio, Luciano C. ; Tronco, Mario L. ; Porto, Arthur J V
Author_Institution :
Mech. Eng. Dept., Univ. of Sao Paulo, Sao Paulo, Brazil
Abstract :
In this project, the main focus is to apply image processing techniques in computer vision 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 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 patterns in which reasonably accurate results were obtained.
Keywords :
agriculture; backpropagation; image colour analysis; image recognition; image segmentation; mobile robots; neurocontrollers; robot vision; statistical analysis; AMR; ANN; HSV space color segments; JSEG image segmentation technique; Matlab-Octave platforms; Simulink environment; agricultural mobile robots; artificial neural networks; cognitive-merged statistical pattern recognition method; computational methods; computer vision; customized backpropagation algorithm; image processing techniques; localization matters; structured heuristics methods; trajectory navigation problems; Artificial neural networks; Classification algorithms; Educational institutions; Image color analysis; Image segmentation; Navigation; Pattern recognition; computer vision; image segmentation; mobile robots; pattern recognition;
Conference_Titel :
Robotics Symposium and Latin American Robotics Symposium (SBR-LARS), 2012 Brazilian
Conference_Location :
Fortaleza
Print_ISBN :
978-1-4673-4650-4
DOI :
10.1109/SBR-LARS.2012.52