Paper
19 July 2013 A MapReduce scheme for image feature extraction and its application to man-made object detection
Fei Cai, Honghui Chen
Author Affiliations +
Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 88782D (2013) https://doi.org/10.1117/12.2031760
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China
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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fei Cai and Honghui Chen "A MapReduce scheme for image feature extraction and its application to man-made object detection", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88782D (19 July 2013); https://doi.org/10.1117/12.2031760
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Cited by 2 scholarly publications.
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KEYWORDS
Feature extraction

Image processing

Edge detection

Parallel computing

Image segmentation

Target detection

Image analysis

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