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Centroiding and classification of objects using a processor array with a scalable region of interest | IEEE Conference Publication | IEEE Xplore

Centroiding and classification of objects using a processor array with a scalable region of interest


Abstract:

In this paper we describe how the location and size of an object in a multi-object scene can be identified and classified using a processor array with a scalable region o...Show More

Abstract:

In this paper we describe how the location and size of an object in a multi-object scene can be identified and classified using a processor array with a scalable region of interest. Objects of interest can be classified by matching them with 25-pixel object prototypes in a window that is adjustable from 17x17 to 5x5. Matlab simulations of the algorithms are shown. In order to carry out the operations effectively, the processor is equipped with a global OR and global sum. Also, the outputs of the row and column decoders can be determined by boundary cell outputs, in addition to the address bits. A 64x64-cell array has been sent to fabrication.
Date of Conference: 18-21 May 2008
Date Added to IEEE Xplore: 13 June 2008
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Conference Location: Seattle, WA, USA

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