19 July 2013 A MapReduce scheme for image feature extraction and its application to man-made object detection
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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.
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Fei Cai, Fei Cai, Honghui Chen, 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); doi: 10.1117/12.2031760; https://doi.org/10.1117/12.2031760
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