Title :
Centroiding and classification of objects using a processor array with a scalable region of interest
Author :
Laiho, Mika ; Poikonen, Jonne ; Paasio, Ari ; Halonen, Kari
Author_Institution :
Microelectron. Lab., Univ. of Turku, Turku
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 17 x 17 to 5 x 5. 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 64 x 64-cell array has been sent to fabrication.
Keywords :
image classification; image matching; microprocessor chips; object recognition; Matlab simulation; column decoders; image matching; object classification; processor array; row decoders; Analog-digital conversion; Cameras; Circuits; Image converters; Image segmentation; Iterative decoding; Laboratories; Layout; Logic programming; Shape control;
Conference_Titel :
Circuits and Systems, 2008. ISCAS 2008. IEEE International Symposium on
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-1683-7
Electronic_ISBN :
978-1-4244-1684-4
DOI :
10.1109/ISCAS.2008.4541740
