Distance Transforms: Academics Versus Industry
نویسندگان
چکیده
منابع مشابه
Distance transforms: Academics versus industry
In image and video analysis, distance transformations (DT) are frequently used. They provide a distance image (DI) of background pixels to the nearest object pixel. DT touches upon the core of many applications; consequently, not only science but also industry has conducted a significant body of work in this field. However, in a vast majority of the cases this has not been published in major sc...
متن کاملMulti-Scale Salience Distance Transforms
The distance transform has been proposed for use in computer vision for a number of applications such as matching and skeletonisation. This paper proposes two things: (1) a multi-scale distance transform to overcome the need to choose edge thresholds and scale and (2) the addition of various saliency factors such as edge strength, length and curvature to the basic distance transform to improve ...
متن کاملDistance Transforms of Sampled Functions
We describe linear-time algorithms for solving a class of problems that involve transforming a cost function on a grid using spatial information. These problems can be viewed as a generalization of classical distance transforms of binary images, where the binary image is replaced by an arbitrary function on a grid. Alternatively they can be viewed in terms of the minimum convolution of two func...
متن کاملRegion Growing Euclidean Distance Transforms
By propagating a vector for each pixel, we show that nearly Euclidean distance maps can be produced quickly by a region growing algorithm using hierarchical queues. Properties of the propagation scheme are used to detect potentially erroneous pixels and correct them by using larger neighbourhoods, without significantly affecting the computation time. Thus, Euclidean distance maps are produced i...
متن کاملAn Objective Comparison Between Gray Weighted Distance Transforms and Weighted Distance Transforms on Curved Spaces
In this paper, we compare two different definitions of distance transform for gray level images: the Gray Weighted Distance Transform (GWDT), and the Weighted Distance Transform On Curved Space (WDTOCS). We show through theoretical and experimental comparisons the differences, the strengths and the weaknesses of these two distances. Continuous case D GW DT = 1 0 |π(t)|dt.
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: Recent Patents on Computer Science
سال: 2011
ISSN: 1874-4796
DOI: 10.2174/1874479611104010001