@Article{cmc.2023.035087,
AUTHOR = {Nihat Arslan, Kali Gurkahraman},
TITLE = {A Novel Contour Tracing Algorithm for Object Shape Reconstruction Using Parametric Curves},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {75},
YEAR = {2023},
NUMBER = {1},
PAGES = {331--350},
URL = {http://www.techscience.com/cmc/v75n1/51484},
ISSN = {1546-2226},
ABSTRACT = {Parametric curves such as Bézier and B-splines, originally developed for the design of automobile bodies, are now also used in image processing and computer vision. For example, reconstructing an object shape in an image, including different translations, scales, and orientations, can be performed using these parametric curves. For this, Bézier and B-spline curves can be generated using a point set that belongs to the outer boundary of the object. The resulting object shape can be used in computer vision fields, such as searching and segmentation methods and training machine learning algorithms. The prerequisite for reconstructing the shape with parametric curves is to obtain sequentially the points in the point set. In this study, a novel algorithm has been developed that sequentially obtains the pixel locations constituting the outer boundary of the object. The proposed algorithm, unlike the methods in the literature, is implemented using a filter containing weights and an outer circle surrounding the object. In a binary format image, the starting point of the tracing is determined using the outer circle, and the next tracing movement and the pixel to be labeled as the boundary point is found by the filter weights. Then, control points that define the curve shape are selected by reducing the number of sequential points. Thus, the Bézier and B-spline curve equations describing the shape are obtained using these points. In addition, different translations, scales, and rotations of the object shape are easily provided by changing the positions of the control points. It has also been shown that the missing part of the object can be completed thanks to the parametric curves.},
DOI = {10.32604/cmc.2023.035087}
}