DocumentCode :
598152
Title :
Rock detection via superpixel graph cuts
Author :
Xiaojin Gong ; Jilin Liu
Author_Institution :
Dept. of Inf. Sci. & Electron. Eng., Zhejiang Univ., Hangzhou, China
fYear :
2012
fDate :
Sept. 30 2012-Oct. 3 2012
Firstpage :
2149
Lastpage :
2152
Abstract :
This paper presents a rock detection method for planetary terrain scenes. Our approach first segments an image into a set of superpixels. Then we formulate the rock detection task as an energy minimization problem and solve it efficiently via a novel graph cut which is constructed on the superpixels. In order to deal with complex rock scenarios, we integrate a discriminative observation model into the graph cut framework to enhance the discrimination power. Meanwhile, a couple of features, for instance, gradient based texture and contextual shading features, are employed to characterize superpixels. With the representative features, as well as the powerful optimization model, the rock detection problem is addressed well. We test our algorithm on a real Lunar terrain image set drawn from NASA which contains diverse scenarios. The attained qualitative and quantitative results show that our algorithm is effective.
Keywords :
feature extraction; geophysical image processing; graph theory; image segmentation; image texture; lunar rocks; object detection; rocks; NASA; complex rock scenarios; contextual shading features; discrimination power enhancement; discriminative observation model; energy minimization problem; gradient based texture; image segmentation; planetary terrain scenes; real Lunar terrain image set; rock detection method; superpixel graph cuts; Accuracy; Feature extraction; Image segmentation; Labeling; Minimization; Moon; Rocks; Adaboost; Rock detection; discriminative learning; graph cut; superpixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
ISSN :
1522-4880
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2012.6467318
Filename :
6467318
Link To Document :
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