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Distance transforms of sampled functions
 Cornell Computing and Information Science
, 2004
"... This paper provides lineartime algorithms for solving a class of minimization problems involving a cost function with both local and spatial terms. These problems can be viewed as a generalization of classical distance transforms of binary images, where the binary image is replaced by an arbitrary ..."
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Cited by 173 (11 self)
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This paper provides lineartime algorithms for solving a class of minimization problems involving a cost function with both local and spatial terms. These problems can be viewed as a generalization of classical distance transforms of binary images, where the binary image is replaced
Distance Transform
, 1748
"... Abstract: A distance transform, also known as distance map or distance field, is a representation of a distance function to an object, as an image. Such maps are used in several applications, especially in document image analysis. Some optimizations can be obtained by less generic methods: for examp ..."
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Abstract: A distance transform, also known as distance map or distance field, is a representation of a distance function to an object, as an image. Such maps are used in several applications, especially in document image analysis. Some optimizations can be obtained by less generic methods
Distance transform
, 2012
"... att atio chia analysis of a single anatomical structure in which the important interstructural information is lost. This paper for constructing a neuroanatomical shape complex atlas based on an information import ..."
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att atio chia analysis of a single anatomical structure in which the important interstructural information is lost. This paper for constructing a neuroanatomical shape complex atlas based on an information import
An efficient euclidean distance transform
 In Combinatorial Image Analysis, IWCIA 2004
, 2004
"... Abstract. Within image analysis the distance transform has many applications. The distance transform measures the distance of each object point from the nearest boundary. For ease of computation, a commonly used approximate algorithm is the chamfer distance transform. This paper presents an efficien ..."
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Cited by 17 (0 self)
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Abstract. Within image analysis the distance transform has many applications. The distance transform measures the distance of each object point from the nearest boundary. For ease of computation, a commonly used approximate algorithm is the chamfer distance transform. This paper presents
The Stepping Distance Transformation
, 1998
"... An algorithm Mscan is proposed for the computation of the distance transform of a feature in an image with respect to a chamfer distance. The algorithm is naively simple and can therefore be easily parallellized. It seems to be new, even for special cases. It is not correct for arbitrary chamfer dis ..."
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An algorithm Mscan is proposed for the computation of the distance transform of a feature in an image with respect to a chamfer distance. The algorithm is naively simple and can therefore be easily parallellized. It seems to be new, even for special cases. It is not correct for arbitrary chamfer
Incremental Distance Transforms (IDT)
"... Abstract—A new generic scheme for incremental implementations of distance transforms (DT) is presented: Incremental Distance Transforms (IDT). This scheme is applied on the cityblock, Chamfer, and three recent exact Euclidean DT (E2DT). A benchmark shows that for all five DT, the incremental imple ..."
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Cited by 1 (1 self)
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Abstract—A new generic scheme for incremental implementations of distance transforms (DT) is presented: Incremental Distance Transforms (IDT). This scheme is applied on the cityblock, Chamfer, and three recent exact Euclidean DT (E2DT). A benchmark shows that for all five DT, the incremental
Generalized distance transforms and skeletons . . .
 IN PROCEEDINGS OF EG/IEEE TCVG SYMPOSIUM ON VISUALIZATION VISSYM ’04
, 2004
"... We present a framework for computing generalized distance transforms and skeletons of twodimensional objects using graphics hardware. Our method is based on the concept of footprint splatting. Combining different splats produces weighted distance transforms for different metrics, as well as the c ..."
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Cited by 4 (0 self)
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We present a framework for computing generalized distance transforms and skeletons of twodimensional objects using graphics hardware. Our method is based on the concept of footprint splatting. Combining different splats produces weighted distance transforms for different metrics, as well
Distance Transformation in Parallel
"... In this paper, we design and implement an efficient parallel algorithm for computing the distance transformation (DT) of a binary image on a PC cluster. The parallel algorithm decomposes the input image into parallelogramlike areas within which a 2pass scanning is performed and among which a wave ..."
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In this paper, we design and implement an efficient parallel algorithm for computing the distance transformation (DT) of a binary image on a PC cluster. The parallel algorithm decomposes the input image into parallelogramlike areas within which a 2pass scanning is performed and among which a wave
The case for approximate Distance Transforms
"... Starting with a binary raster, the calculation of exact Euclidean distance from the foreground pixels (1elements) to the background pixels (0elements) is a simple yet timeconsuming operation. Elsewhere it is argued that for some applications (such as pattern recognition and robotics for example) ..."
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Cited by 2 (0 self)
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) the calculation of approximate Euclidean distance is a viable, quick and efficient alternative solution. There has been much research on a number of innovative approximate distance transforms. The vast majority of these have been reported in the computer science and mathematical literature, and yet given its
Optimum design of chamfer distance transforms
 IEEE TRANS. IMAGE PROCESSING
, 1998
"... The distance transform has found many applications in image analysis. Chamfer distance transforms are a class of discrete algorithms that offer a good approximation to the desired Euclidean distance transform at a lower computational cost. They can also give integervalued distances that are more s ..."
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Cited by 30 (2 self)
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The distance transform has found many applications in image analysis. Chamfer distance transforms are a class of discrete algorithms that offer a good approximation to the desired Euclidean distance transform at a lower computational cost. They can also give integervalued distances that are more
Results 1  10
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