This paper proposes a massively parallel line feature extraction technique for 2D images. This new scheme uses a modified Hough transform implemented in a massively parallel fashion to extract the line features in an input image. The algorithm is based on the recursive decomposition technique. A parallel Hough transform detects line segments in the subimages of the input image. A bottom up approach then merges these line segments into longer lines. A pointerless tree structure is utilized to store feature information at various levels of the merging process. The line segment merging process is equivalent to climbing the tree representing the line features in the entire image. Techniques for line feature merging and balancing of features, tradeoffs between determination of line properties and computation, and algorithmic complexity are addressed in detail.
[1]
Sartaj Sahni,et al.
Hypercube Algorithms: with Applications to Image Processing and Pattern Recognition
,
1990
.
[2]
Jack Sklansky,et al.
Finding circles by an array of accumulators
,
1975,
Commun. ACM.
[3]
M. Shneier.
Calculations of geometric properties using quadtrees
,
1981
.
[4]
Josef Kittler,et al.
A hierarchical approach to line extraction
,
1989,
Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[5]
Richard O. Duda,et al.
Use of the Hough transformation to detect lines and curves in pictures
,
1972,
CACM.