IEICE TRANSACTIONS on Information
A New Integral Image Structure for Memory Size Reduction
Summary :
An integral image is the sum of input image pixel values. It is mainly used to speed up the process of a box filter operation, such as Haar-like features. However, large memory for integral image data can be an obstacle in an embedded environment with limited hardware. Therefore, an efficient method to store the integral image is necessary. In this paper, we propose a memory size reduction method for integral image. The method uses four types image information: an integral image, a row integral image, a column integral image, and an input image. Using this method, integral image memory can be reduced by 42.6% on a 640×480 8-bit gray-scale input image. The same idea can be applied for bigger size images.
- Publication
- IEICE TRANSACTIONS on Information Vol.E97-D No.4 pp.998-1000
- Publication Date
- 2014/04/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E97.D.998
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Su-hyun LEE
Kwangwoon University
Yong-jin JEONG
Kwangwoon University
Keyword
Latest Issue
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Su-hyun LEE, Yong-jin JEONG, "A New Integral Image Structure for Memory Size Reduction" in IEICE TRANSACTIONS on Information,
vol. E97-D, no. 4, pp. 998-1000, April 2014, doi: 10.1587/transinf.E97.D.998.
Abstract: An integral image is the sum of input image pixel values. It is mainly used to speed up the process of a box filter operation, such as Haar-like features. However, large memory for integral image data can be an obstacle in an embedded environment with limited hardware. Therefore, an efficient method to store the integral image is necessary. In this paper, we propose a memory size reduction method for integral image. The method uses four types image information: an integral image, a row integral image, a column integral image, and an input image. Using this method, integral image memory can be reduced by 42.6% on a 640×480 8-bit gray-scale input image. The same idea can be applied for bigger size images.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E97.D.998/_p
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@ARTICLE{e97-d_4_998,
author={Su-hyun LEE, Yong-jin JEONG, },
journal={IEICE TRANSACTIONS on Information},
title={A New Integral Image Structure for Memory Size Reduction},
year={2014},
volume={E97-D},
number={4},
pages={998-1000},
abstract={An integral image is the sum of input image pixel values. It is mainly used to speed up the process of a box filter operation, such as Haar-like features. However, large memory for integral image data can be an obstacle in an embedded environment with limited hardware. Therefore, an efficient method to store the integral image is necessary. In this paper, we propose a memory size reduction method for integral image. The method uses four types image information: an integral image, a row integral image, a column integral image, and an input image. Using this method, integral image memory can be reduced by 42.6% on a 640×480 8-bit gray-scale input image. The same idea can be applied for bigger size images.},
keywords={},
doi={10.1587/transinf.E97.D.998},
ISSN={1745-1361},
month={April},}
Copy
TY - JOUR
TI - A New Integral Image Structure for Memory Size Reduction
T2 - IEICE TRANSACTIONS on Information
SP - 998
EP - 1000
AU - Su-hyun LEE
AU - Yong-jin JEONG
PY - 2014
DO - 10.1587/transinf.E97.D.998
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2014
AB - An integral image is the sum of input image pixel values. It is mainly used to speed up the process of a box filter operation, such as Haar-like features. However, large memory for integral image data can be an obstacle in an embedded environment with limited hardware. Therefore, an efficient method to store the integral image is necessary. In this paper, we propose a memory size reduction method for integral image. The method uses four types image information: an integral image, a row integral image, a column integral image, and an input image. Using this method, integral image memory can be reduced by 42.6% on a 640×480 8-bit gray-scale input image. The same idea can be applied for bigger size images.
ER -
English
