Revisiting the medial axis for planar shape decomposition
نویسندگان
چکیده
منابع مشابه
Planar shape decomposition made simple
THE psychophysical, ecological, and computational aspects of planar shape decomposition into parts have been studied for more than five decades [9]. Although a complete theory of object recognition remains an impossibility, it is believed that our ability to recognize objects by their silhouette alone is related to simple rules by which the visual system decomposes shapes into parts [4]. In com...
متن کاملPAPANELOPOULOS, AVRITHIS: PLANAR SHAPE DECOMPOSITION MADE SIMPLE 1 Planar shape decomposition made simple
We present a very simple computational model for planar shape decomposition that naturally captures most of the rules and salience measures suggested by psychophysical studies, including the minima and short-cut rules, convexity, and symmetry. It is based on a medial axis representation in ways that have not been explored before and sheds more light into the connection between existing rules li...
متن کاملMedial axis computation for planar free-form shapes
We present a simple, efficient, and stable method for computing—with any desired precision—the medial axis of simply connected planar domains. The domain boundaries are assumed to be given as polynomial spline curves. Our approach combines known results from the field of geometric approximation theory with a new algorithm from the field of computational geometry. Challenging steps are (1) the a...
متن کاملFarey Sequences and the Planar Euclidean Medial Axis Test Mask
The Euclidean test mask T (r) is the minimum neighbourhood sufficient to detect the Euclidean Medial Axis of any discrete shape whose inner radius does not exceed r. We establish a link between T (r) and the well-known Farey sequences, which allows us to propose two new algorithms. The first one computes T (r) in time O(r) and space O(r). The second one computes for any vector − →v the smallest...
متن کاملA Generalized Shape-Axis Model for Planar Shapes
We describe a generalized shape-axis (SA) model for representing both open and closed planar curves. The SA model is an effective way to represent shapes by comparing their self-similarities. Given a 2D shape, whether it is closed or open, we use two different parameterizations (one parameterization is oriented clockwise and the other counterclockwise) for the curve. To study the self-similarit...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computer Vision and Image Understanding
سال: 2019
ISSN: 1077-3142
DOI: 10.1016/j.cviu.2018.10.007