This report describes a technique to detect curvature. The technique uses local polynomial fitting on a local orientation description of an image. The idea is based on the theory of rotational symmetries which describes curvature, circles, starpatterns etc. The local polynomial fitting is shown to be equivalent to calculating partial derivatives on a lowpass version of the local orientation. Th...

A method for automatic assessment of singing voice is proposed. Such method quantifies in a meaningful way the similarity between the user performance and a reference melody. A set of melodic similarity measures comprising intonation and rhythmic aspects have been implemented for this goal. Such measure implement different MIR techniques, such as melodic transcription or score alignment. The re...

We introduce the extension of local polynomial fitting to the linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the t...

Atomic force microscopy (AFM) images normally exhibit various artifacts. As a result, image flattening is required prior to image analysis. To obtain optimized flattening results, foreground features are generally manually excluded using rectangular masks in image flattening, which is time consuming and inaccurate. In this study, a two-step scheme was proposed to achieve optimized image flatten...

In seismic data processing, random noise seriously affects the seismic data quality and subsequently the interpretation. This study aims to increase the signal-tonoise ratio by suppressing random noise and improve the accuracy of seismic data interpretation without losing useful information. Hence, we propose a structureoriented polynomial fitting filter. At the core of structure-oriented filte...

We propose a linear-time algorithm for curve segmentation which is based on constructive polynomial fitting. This work extends previous work on constructive fitting by taking the topological properties of a digitized curve into account. The algorithm uses uniform (or L∞) fitting and it works for segments of arbitrary thickness. We illustrate the algorithm with the segmentation of contours into ...