Title :
ANN statistical image recognition method for computer vision in agricultural 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 :
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.
Keywords :
agriculture; image classification; image recognition; mobile robots; multilayer perceptrons; navigation; neural nets; robot vision; ANN statistical image recognition method; HSV space color segments; JSEG algorithm; agricultural mobile robot navigation; artificial neural networks; back-propagation multilayer perceptron algorithm; computer vision; omnidirectional vision system; statistical methods; Artificial neural networks; Cameras; Classification algorithms; Image color analysis; Image segmentation; Mirrors; Support vector machine classification; artificial neural networks; computer vision; image recognition and processing; mobile robots;
Conference_Titel :
Mechatronics and Automation (ICMA), 2010 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-5140-1
Electronic_ISBN :
2152-7431
DOI :
10.1109/ICMA.2010.5588694