840 resultados para BAJA VISION - INVESTIGACIONES
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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.
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The influence of the type of rotary cutting instrument on bone repair after osteotomy in swine jaw, was evaluated using digital and densitometric radiographic examinations, at controlled times. Two cross-sectional dissections were made through the base of the right jaw, one using a high speed rotary instrument and the other using low speed, both with liquid cooling. After established periods the animals were sacrificed and their jaws removed for direct and indirect digital radiographic and densitometric studies using the CROMOX, DIGORA and ODR systems. In the initial periods (7 and 28 days) the bone density was higher in osteotomy areas performed with high rotation speeds, and in the final periods (60 and 90 days) the bone density was higher in the osteotomies performed with low rotation, indicating a better final bone repair with the use of low rotation. The qualitative analysis of the repair process was made by the ODR system which obtained three-dimensional and coloured digital images, which enable the bone thickness to be measured using an aluminium wedge. This showed that by twenty-eight days the bone repair was already apparently complete. © 2010 SECOM.
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ANN statistical image recognition method for computer vision in agricultural mobile robot navigation
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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. © 2010 IEEE.
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