NIST Technical NoteU.S. Department of Commerce, National Institute of Standards and Technology, 1989 |
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... applied science in support of these efforts ; builds and maintains competence in the necessary disciplines required to carry out this research and technical service ; develops engi- neering data and measurement capabilities ; provides ...
... applied science in support of these efforts ; builds and maintains competence in the necessary disciplines required to carry out this research and technical service ; develops engi- neering data and measurement capabilities ; provides ...
Page 5
... applied at Level 1. Appendix B describes edge point extraction al- gorithms , surface patch or region extraction algorithms , and the first level of optical flow ex- traction algorithms . 2. General System Architecture Before describing ...
... applied at Level 1. Appendix B describes edge point extraction al- gorithms , surface patch or region extraction algorithms , and the first level of optical flow ex- traction algorithms . 2. General System Architecture Before describing ...
Page 9
... applied . It may be appropriate for a specific application to perform temporal integration after spatial integration , such as when tracking a centroid of a moving object , or it may be un- necessary to do either spatial or temporal ...
... applied . It may be appropriate for a specific application to perform temporal integration after spatial integration , such as when tracking a centroid of a moving object , or it may be un- necessary to do either spatial or temporal ...
Page 26
7. Appendix A : Preprocessing Techniques This section discusses preprocessing techniques that are applied in the sensor process- ing module of Level 1 of the perception hierarchy . The input to these algorithms is consid- ered to be an ...
7. Appendix A : Preprocessing Techniques This section discusses preprocessing techniques that are applied in the sensor process- ing module of Level 1 of the perception hierarchy . The input to these algorithms is consid- ered to be an ...
Page 30
... applied over all points in the image is an example of a low - pass filter which reduces noise in those parts of an image where there are no strong edges . A side effect of this operation is that portions of the image containing a large ...
... applied over all points in the image is an example of a low - pass filter which reduces noise in those parts of an image where there are no strong edges . A side effect of this operation is that portions of the image containing a large ...
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Common terms and phrases
algorithm command algorithm parameters Appendix Architecture Artificial Intelligence averaging binary blurred camera class of algorithms command number Execution Comparator Module Computer Computer Vision Corner Detection described edge detection Engineering enhancement Execution command number Execution module Figure frequency functions Gaithersburg global data system GONZA77 grey level hierarchy High-Pass Filtering histogram IEEE Image Processing input Institute of Standards intensity Job Assignment module Level 1 Job Level 1 Sensory Level 1 Task low-pass Low-Pass Filtering manipulator mask measure methods module receives neighborhood NIST number Execution status object optical flow output performed pixels Planner module Precision requirements Priority preprocessing technique priority level assigned queue Robotics ROSEN82 segmentation selected algorithm sensory processing module sensory processing system SP WM TD spatial integrator specified Standards and Technology step edge surface patch Tactile Task Decomposition interface task decomposition module Telerobot texture threshold value tion update Visual Perception world model global World Modeling Interface
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