ETRI-Knowledge Sharing Plaform

KOREAN
논문 검색
Type SCI
Year ~ Keyword

Detail

Journal Article The Computation Reduction in Object Detection via Composite Structure of Modified Integral Images
Cited 0 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Daeha LEE, Jaehong KIM, Ho-Hee KIM, Soon-Ja KIM
Issue Date
2017-01
Citation
IEICE Transactions on Information and Systems, v.E100.D, no.1, pp.229-233
ISSN
1745-1361
Publisher
일본, 전자정보통신학회 (IEICE)
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1587/transinf.2016EDL8158
Abstract
Object detection is the first step in the object recognition. According to the detection results, its following works are affected. However, object detection has a heavy resource requirement in terms of, computing power and memory. If an image is enlarged, the computational load required for object detection is also increased. An-integral-image-based method guarantees fast object detection. Once an integral image is generated, the speed of the object detection procedure remains fixed, regardless of the pattern region size. However, this becomes an even greater issue if the image is enlarged. In this paper, we propose the use of directional integral image based object detection. A directional integral image gives direction to an integral image, which can then be calculated from various directions. Furthermore, many unnecessary calculations, which typically occur when a partial integral image is used for object detection, can be avoided. Therefore, the amount of computation is reduced, compared with methods using integral images. In experiments comparing methods, the proposed method required 40% fewer computations.
KSP Keywords
Computing power, Detection procedure, Image-based method, Integral Image, Object Recognition, Object detection, composite structure, computation reduction, computational load