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Proceedings Paper

A MapReduce scheme for image feature extraction and its application to man-made object detection
Author(s): Fei Cai; Honghui Chen
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Paper Abstract

A fundamental challenge in image engineering is how to locate interested objects from high-resolution images with efficient detection performance. Several man-made objects detection approaches have been proposed while the majority of these methods are not truly timesaving and suffer low degree of detection precision. To address this issue, we propose a novel approach for man-made object detection in aerial image involving MapReduce scheme for large scale image analysis to support image feature extraction, which can be widely used to compute-intensive tasks in a highly parallel way, and texture feature extraction and clustering. Comprehensive experiments show that the parallel framework saves voluminous time for feature extraction with satisfied objects detection performance.

Paper Details

Date Published: 19 July 2013
PDF: 7 pages
Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88782D (19 July 2013); doi: 10.1117/12.2031760
Show Author Affiliations
Fei Cai, National Univ. of Defense Technology (China)
Honghui Chen, National Univ. of Defense Technology (China)

Published in SPIE Proceedings Vol. 8878:
Fifth International Conference on Digital Image Processing (ICDIP 2013)
Yulin Wang; Xie Yi, Editor(s)

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