1 August 1990 Hierarchical object boundary detection and description
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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.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
WenThong Chang, Kai-Hsiang Chou, "Hierarchical object boundary detection and description", Proc. SPIE 1251, Curves and Surfaces in Computer Vision and Graphics, (1 August 1990); doi: 10.1117/12.19742; https://doi.org/10.1117/12.19742

Edge detection

Image segmentation

Computer graphics

Computer vision technology

Machine vision

Feature extraction



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