NIST Technical NoteU.S. Department of Commerce, National Institute of Standards and Technology, 1989 |
From inside the book
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Page 8
... threshold ( fig . 5 ) . A specific exam- ple of how these modules interact at a given level is given in section 3.2 , where the sensory processing module at Level 1 is discussed . ↑ Detection Threshold Spatial Integrator Temporal ...
... threshold ( fig . 5 ) . A specific exam- ple of how these modules interact at a given level is given in section 3.2 , where the sensory processing module at Level 1 is discussed . ↑ Detection Threshold Spatial Integrator Temporal ...
Page 9
... threshold , indicating correspondence between observations and the prediction of the world model , event detection occurs . An event can be defined to be the detection of an edge point , the fit of a line , or the recognition of an ...
... threshold , indicating correspondence between observations and the prediction of the world model , event detection occurs . An event can be defined to be the detection of an edge point , the fit of a line , or the recognition of an ...
Page 10
... threshold value used in edge detection or a window for the centroid value of a moving object are two examples . The results of the sensory processing integration and detection processes are sent to the world model where they are used to ...
... threshold value used in edge detection or a window for the centroid value of a moving object are two examples . The results of the sensory processing integration and detection processes are sent to the world model where they are used to ...
Page 18
... threshold parameter stored in the world model . Pixels which exceed this threshold value are labelled edge points , while those pixels falling below the threshold are labelled non - edge points . 3.3 . Level 1 World Model Input to world ...
... threshold parameter stored in the world model . Pixels which exceed this threshold value are labelled edge points , while those pixels falling below the threshold are labelled non - edge points . 3.3 . Level 1 World Model Input to world ...
Page 19
... threshold value n ΣΣ t = mij = m f ( x + i , y + j ) size of spatial window n Σf ( x , y , t ) t - m size of temporal integration 2 0 algorithm name predicted edge mask 2 -1 C - 1 intensity pixel intensity pixel intensity pixel Figure ...
... threshold value n ΣΣ t = mij = m f ( x + i , y + j ) size of spatial window n Σf ( x , y , t ) t - m size of temporal integration 2 0 algorithm name predicted edge mask 2 -1 C - 1 intensity pixel intensity pixel intensity pixel Figure ...
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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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