Novel Hardware Algorithms for Row-Parallel Integral Image Calculation
Novel Hardware Algorithms for Row-Parallel Integral Image Calculation
The integral image is an intermediate image representation that allows rapid calculation of rectangular features at constant speed, irrespective of filter size, and is particularly useful for multi-scale computer vision algorithms like speeded-up robust features (SURF). Although calculation of the integral image involves simple addition operations, the total number of operations is significant due to the generally large size of image data. Recursive equations allow considerable reduction in the required number of addition operations but require calculation of the integral image in a serial fashion. This is generally not desirable for real-time embedded vision systems with strict time limitations and low-powered but parallel hardware resources. With the objective of minimizing the hardware resources involved, this paper proposes two novel hardware algorithms based on decomposition of these recursive equations, allowing calculation of up to four integral image values in a row-parallel way with out significantly increasing the number of addition operations.
61-65
Ehsan, Shoaib
ae8922f0-dbe0-4b22-8474-98e84d852de7
Clark, Adrian F.
81c08359-a1fe-4380-adc0-2da681e19df0
McDonald-Maier, Klaus D.
d35c2e77-744a-4318-9d9d-726459e64db9
2009
Ehsan, Shoaib
ae8922f0-dbe0-4b22-8474-98e84d852de7
Clark, Adrian F.
81c08359-a1fe-4380-adc0-2da681e19df0
McDonald-Maier, Klaus D.
d35c2e77-744a-4318-9d9d-726459e64db9
Ehsan, Shoaib, Clark, Adrian F. and McDonald-Maier, Klaus D.
(2009)
Novel Hardware Algorithms for Row-Parallel Integral Image Calculation.
In,
2009 Digital Image Computing: Techniques and Applications: (DICTA 2009).
Digital Image Computing: Techniques and Applications (01/12/09 - 03/12/09)
IEEE, .
(doi:10.1109/DICTA.2009.20).
Record type:
Book Section
Abstract
The integral image is an intermediate image representation that allows rapid calculation of rectangular features at constant speed, irrespective of filter size, and is particularly useful for multi-scale computer vision algorithms like speeded-up robust features (SURF). Although calculation of the integral image involves simple addition operations, the total number of operations is significant due to the generally large size of image data. Recursive equations allow considerable reduction in the required number of addition operations but require calculation of the integral image in a serial fashion. This is generally not desirable for real-time embedded vision systems with strict time limitations and low-powered but parallel hardware resources. With the objective of minimizing the hardware resources involved, this paper proposes two novel hardware algorithms based on decomposition of these recursive equations, allowing calculation of up to four integral image values in a row-parallel way with out significantly increasing the number of addition operations.
This record has no associated files available for download.
More information
Published date: 2009
Venue - Dates:
Digital Image Computing: Techniques and Applications, , Melbourne, Australia, 2009-12-01 - 2009-12-03
Identifiers
Local EPrints ID: 478890
URI: http://eprints.soton.ac.uk/id/eprint/478890
PURE UUID: 385aacab-223e-4898-8962-48a0b75ad116
Catalogue record
Date deposited: 12 Jul 2023 16:40
Last modified: 17 Mar 2024 04:16
Export record
Altmetrics
Contributors
Author:
Shoaib Ehsan
Author:
Adrian F. Clark
Author:
Klaus D. McDonald-Maier
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics