Abstract
Template matching is a very topical issue in a wide range of imagining applications. Automated detection of features such as building roof for template matching and pattern recognition is great significance in the image processing field. In this chapter, a method which is developed optimizing the shape and size of hit-or-miss morphological filtering parameters with morphological operators is presented for building roof target detection. Morphological operations of opening and closing with constructions are applied to segmented images. Hit-or-Miss Transform (HMT) has been successfully applied for template matching in binary images. The proposed approach involves several advanced morphological operators among which an adaptive HMT with varying size and shape of the structuring elements. VHR space borne images consisting of a pre and post 2011 Pacific coast of Tohoku earthquake and the tsunami site of the Ishinomaki, Miyagi area in Japan were used. Experimental results show that the identified probability of building can reach more than 81 % by this method.
| Original language | English |
|---|---|
| Pages (from-to) | 641-650 |
| Number of pages | 10 |
| Journal | International Journal of Machine Learning and Cybernetics |
| Volume | 6 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2015 Aug 24 |
| Externally published | Yes |
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Keywords
- Airborne VHR images
- Building extraction
- HMT
- Mathematical morphological profile
- Natural hazard
ASJC Scopus subject areas
- Artificial Intelligence
- Software
- Computer Vision and Pattern Recognition
Cite this
Optimization of structure elements for morphological hit-or-miss transform for building extraction from VHR airborne imagery in natural hazard areas. / Parape, Chandana Dinesh; Premachandra, Chinthaka; Tamura, Masayuki.
In: International Journal of Machine Learning and Cybernetics, Vol. 6, No. 4, 24.08.2015, p. 641-650.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Optimization of structure elements for morphological hit-or-miss transform for building extraction from VHR airborne imagery in natural hazard areas
AU - Parape, Chandana Dinesh
AU - Premachandra, Chinthaka
AU - Tamura, Masayuki
PY - 2015/8/24
Y1 - 2015/8/24
N2 - Template matching is a very topical issue in a wide range of imagining applications. Automated detection of features such as building roof for template matching and pattern recognition is great significance in the image processing field. In this chapter, a method which is developed optimizing the shape and size of hit-or-miss morphological filtering parameters with morphological operators is presented for building roof target detection. Morphological operations of opening and closing with constructions are applied to segmented images. Hit-or-Miss Transform (HMT) has been successfully applied for template matching in binary images. The proposed approach involves several advanced morphological operators among which an adaptive HMT with varying size and shape of the structuring elements. VHR space borne images consisting of a pre and post 2011 Pacific coast of Tohoku earthquake and the tsunami site of the Ishinomaki, Miyagi area in Japan were used. Experimental results show that the identified probability of building can reach more than 81 % by this method.
AB - Template matching is a very topical issue in a wide range of imagining applications. Automated detection of features such as building roof for template matching and pattern recognition is great significance in the image processing field. In this chapter, a method which is developed optimizing the shape and size of hit-or-miss morphological filtering parameters with morphological operators is presented for building roof target detection. Morphological operations of opening and closing with constructions are applied to segmented images. Hit-or-Miss Transform (HMT) has been successfully applied for template matching in binary images. The proposed approach involves several advanced morphological operators among which an adaptive HMT with varying size and shape of the structuring elements. VHR space borne images consisting of a pre and post 2011 Pacific coast of Tohoku earthquake and the tsunami site of the Ishinomaki, Miyagi area in Japan were used. Experimental results show that the identified probability of building can reach more than 81 % by this method.
KW - Airborne VHR images
KW - Building extraction
KW - HMT
KW - Mathematical morphological profile
KW - Natural hazard
UR - http://www.scopus.com/inward/record.url?scp=84937932816&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84937932816&partnerID=8YFLogxK
U2 - 10.1007/s13042-014-0326-1
DO - 10.1007/s13042-014-0326-1
M3 - Article
AN - SCOPUS:84937932816
VL - 6
SP - 641
EP - 650
JO - International Journal of Machine Learning and Cybernetics
JF - International Journal of Machine Learning and Cybernetics
SN - 1868-8071
IS - 4
ER -