NIST Technical NoteU.S. Department of Commerce, National Institute of Standards and Technology, 1989 |
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... B8.2.1 . Intensity and Color ......... B8.2.2 . Texture B8.3 . Optical Flow ...... B8.4 . Evaluation ............. 32 .... 34 34 34 .... 37 39 40 40 40 41 42 1. Introduction The telerobot control system architecture discussed in [ iv.
... B8.2.1 . Intensity and Color ......... B8.2.2 . Texture B8.3 . Optical Flow ...... B8.4 . Evaluation ............. 32 .... 34 34 34 .... 37 39 40 40 40 41 42 1. Introduction The telerobot control system architecture discussed in [ iv.
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... texture information is not visible , and does not have to be smoothed from the image . However , tex- ture could be visible in a closer view of the same object and must be removed in order to avoid false edge information . Thus ...
... texture information is not visible , and does not have to be smoothed from the image . However , tex- ture could be visible in a closer view of the same object and must be removed in order to avoid false edge information . Thus ...
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... . [ DAVIS86 ] Davis , L. S. , " Image Texture Analysis Techniques - A Survey " , Vision and Information Processing for Automation , Arthur Browne , ed . , Plenum Press , New York , 1986 . [ DORF83 ] Dorf , R. C. , 22.
... . [ DAVIS86 ] Davis , L. S. , " Image Texture Analysis Techniques - A Survey " , Vision and Information Processing for Automation , Arthur Browne , ed . , Plenum Press , New York , 1986 . [ DORF83 ] Dorf , R. C. , 22.
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... , A. P. , " Recovering Surface Shape and Orientation from Texture " , Ar- tificial Intelligence , Vol . 17 , Nos . 1-3 , August 1981 , pp . 17-46 . 7. Appendix A : Preprocessing Techniques This section discusses preprocessing 25.
... , A. P. , " Recovering Surface Shape and Orientation from Texture " , Ar- tificial Intelligence , Vol . 17 , Nos . 1-3 , August 1981 , pp . 17-46 . 7. Appendix A : Preprocessing Techniques This section discusses preprocessing 25.
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... texture . Marr [ MARR81 ] present methods for choosing the appropriate span . Using these ideas , Nevatia and Babu [ NEVAT80 ] use six 5x5 masks that correspond to an ideal step edge at various 30 ° orientations : -100 100 b 100 100 ...
... texture . Marr [ MARR81 ] present methods for choosing the appropriate span . Using these ideas , Nevatia and Babu [ NEVAT80 ] use six 5x5 masks that correspond to an ideal step edge at various 30 ° orientations : -100 100 b 100 100 ...
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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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