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ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

机译:农业移动机器人导航中计算机视觉的神经网络统计图像识别方法

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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.
机译:该项目的主要应用领域是通过全向视觉系统将计算机视觉中的图像处理和分割技术部署到用于轨迹导航问题和定位问题的农业移动机器人(AMR)。因此,基于JSEG算法的计算方法被用于提供此类问题的分类和特征,以及用于图像识别的人工神经网络(ANN)。因此,可以通过Matlab / Octave计算平台进行仿真并对JSEG图像分割技术的性能进行分析,并结合使用定制的反向传播多层感知器(MLP)算法和统计方法作为结构化启发式方法, Simulink环境。完成上述步骤后,对HSV空间颜色段进行分类和特征化是可行的,更不用说允许对获得合理准确结果的分割图像进行识别了。

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