Hierarchical object boundary detection and description
Wen-Thong Chang, Kai-Hsiang Chou · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
In this paper, we discuss a hierarchical method for object boundary detection and description for a gray-level image. Lower level algorithms focus on the object boundary detection, and higher level algorithms focus on the boundary feature extraction and description. A one pixel wide close-form boundary is first extracted by recursive histogram-based binarization. The histogram is formed with the graylevels of an initial set of edge points obtained by a gradient operator. The purpose of this approach is to facilitate the selection of a set of good corner points. With this set of corner points, a parametric description of the object boundary is generated. In the high level representation, a cubic spline curve between every two boundary corner points is generated. The entire object boundary can then be represented as the connection of a set of spline curve. Since a cubic spline curve needs only 4 parameters, the final representation of the object boundary is very efficient. Difference between the close-form boundary by recursive binarization and the spline representattion is also compared and discussed.