Calculation of a Threshold for Decision of Similar Features in Different Spatial Data Sets
이종의 공간 데이터 셋에서 매칭 객체 판별을 위한 임계값 산출

Jiyoung Kim, Yong Huh, Kiyun Yu, Jung Ok Kim
2013 Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography  
The process of a feature matching for two different spatial data sets is similar to the process of classification as a binary class such as matching or non-matching. In this paper, we calculated a threshold by applying an equal error rate (EER) which is widely used in biometrics that classification is a main topic into spatial data sets. In a process of discriminating what's a matching or what's not, a precision and a recall is changed and a trade-off appears between these indexes because the
more » ... mber of matching pairs is changed when a threshold is changed progressively. This trade-off point is EER, that is, threshold. To the result of applying this method into training data, a threshold is estimated at 0.802 of a value of shape similarity. By applying the estimated threshold into test data, F-measure that is a evaluation index of matching method is highly value, 0.940. Therefore we confirmed that an accurate threshold is calculated by EER without person intervention and this is appropriate to matching different spatial data sets.
doi:10.7848/ksgpc.2013.31.1.23 fatcat:5oui24shzfd3taxon7o2jb74zu