Real-time line detection using accelerated high-resolution Hough transform
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Real-time detection of lines using parallel coordinates and CUDA
Journal of Real-Time Image Processing
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Dynamically Quantized (DO) spaces have been developed [O'Rourke] in response to the need for high-precision, high-dimensional Hough-like transforms. [Ballard; Sloan and Ballard) Their purpose is to cover a parameter space with a limited number of accumulators in such a way that fine precision is maintained where it is needed. O'Rourke's solution to this problem is to maintain a binary tree of cells. Each cell covers an n-dimensional rectangular region of the space. Under certain conditions, the cell may be split along a particular dimension, and two sons created. Under complementary conditions, sets of cells may merge. Cell splitting is relatively simple, but the process of cell merging is quite complicated, for reasons which are explored extensively in [O'Rourke]. The solution presented here is based on a pyramid data structure, in which the number and connectivity (between fathers and sons) of cells is fixed. This data structure has the advantage that its resource allocation is fixed, and the cells and their connections may be reduced to a hardware implementation (e.g., in VLSI.) The customary difficulty with the pyramid is that the boundaries of the cells (and hence the spatial resolution) are fixed, also. In this Dynamically Quantized Pyramid (DQP), the boundaries of the cells are continually modified by means of a hierarchical warping process. Essentially, each cell tries to track the mean position of data points in its part of the space. This estimate of the local mean is used to define the boundaries of the cell's sons. An experimental implementation has been built and subjected to various distributions (spatial and temporal) of data. The resulting quantizations are shown and discussed.