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
N1 - Funding Information:
We would like to thank for giving access to the airborne imagery and GIS data, provided by the Geospatial Information Authority of Japan (GSI). This study was partially supported by Setsutaro Kobayashi memorial foundation.
Publisher Copyright:
© 2015, Springer-Verlag Berlin Heidelberg.
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
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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 -