For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Optical Flow Detection System Using a Parallel Processor NEURO4
Jun TAKEDA Ken-ichi TANAKA Kazuo KYUMA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1998/03/25
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section of Selected Papers from the 10th Karuizawa Workshop on Circuits and Systems)
optical flow, moving image recognition, neural network, parallel processing, SIMD,
Full Text: PDF(604.9KB)>>
An image recognition system using NEURO4, a programmable parallel processor, is described. Optical flow is the velocity field that an observer detects on a two-dimensional image and gives useful information, such as edges, about moving objects. The processing time for detecting optical flow on the NEURO4 system was analyzed. Owing to the parallel computation scheme, the processing time on the NEURO4 system is proportional to the square root of the size of images, while conventional sequential computers need time in proportion to the size. This analysis was verified by experiments using the NEURO4 system. When the size of an image is 84 84, the NEURO4 system can detect optical flow in less than 10 seconds. In this case the NEURO4 system is 23 times faster than a workstation, Sparc Station 20 (SS20). The larger the size of images becomes, the faster the NEURO4 system can detect optical flow than conventional sequential computers like SS20. Furthermore, the paralleling effect increases in proportion to the number of connected NEURO4 chips by a ring expansion scheme. Therefore, the NEURO4 system is useful for developing moving image recognition algorithms which require a large amount of processing time.