A novel method for determination of best ordering direction for noisy point clouds

International Symposium on Innovations in Intelligent Systems and Applications, Trabzon, Turkey, 2 - 04 July 2012, pp.1-5

In this paper, we propose a method to determine the

best regression axis to order the noisy points for curve

reconstruction. The fundamental problem of the curve

reconstruction is to order the data in most suitable way. We

suggested a histogram based feature to be able to determine the

goodness of the order for a regression line. The method developed

by using the proposed feature tested on the some synesthetic data

with different noise levels. This data was selected due to the

eigenvector approach gave wrong results when obtaining

regression line. The results showed that the proposed method is

encouraging.