DocumentCode :
3064728
Title :
Efficient use of parallelism in intermediate level vision tasks
Author :
Gerogiannis, Dimitris ; Orphanoudakis, Stelios C.
Author_Institution :
Daimler Benz AG, Berlin, Germany
fYear :
1992
fDate :
30 Aug-3 Sep 1992
Firstpage :
160
Lastpage :
164
Abstract :
The primary task of intermediate level vision (ILV) is to take the output of low level vision, which is typically a subset of pixels from the original image array, and to generate a representation of image content which is appropriate for symbolic manipulations at a higher level. These tasks, e.g. boundary detection, various types of segmentation or the computation of attributes of image components, involve operations on individual pixels, sets of pixels with a common label or on entities extracted from the raw pixel data, such as orientation of lines or distance between pairs of parallel lines. A class of tasks which operate on individual pixels or sets of pixels is described, problems which are raised in parallel implementations of this class of tasks are considered, and solutions are suggested
Keywords :
computer vision; feature extraction; image segmentation; parallel algorithms; boundary detection; intermediate level vision; orientation; parallel implementations; parallel lines; raw pixel data; segmentation; symbolic manipulations; Appropriate technology; Computer science; Computer vision; Concurrent computing; Costs; Data mining; Data structures; Image segmentation; Parallel processing; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1992. Vol. IV. Conference D: Architectures for Vision and Pattern Recognition, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2925-8
Type :
conf
DOI :
10.1109/ICPR.1992.202156
Filename :
202156
Link To Document :
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