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Title: Memory compression for straight line recognition using the Hough transform
Authors: Ser, PK
Siu, WC 
Keywords: Hough transform
Line detection
Region bit map (RBM)
Sub-image voting
Issue Date: 1995
Publisher: North-Holland
Source: Pattern recognition letters, 1995, v. 16, no. 2, p. 133-145 How to cite?
Journal: Pattern recognition letters 
Abstract: In this paper, we introduce a novel technique for memory compression of the Hough transform. Our approach is to partition an image into many sub-images, and there is no need to iterate the line detection with different levels of hierarchical line finding. On the average, our algorithm only requires a few seconds for the extraction of global edges for images with 384*256 pixels using a 33 MHz 486 machine. Besides the reduction of processing time as comparing with the conventional approach, a 50% reduction of the conventional memory requirement can also be achieved for partitioning the image into 16 sub-images. The novel Hough domain consists of two parts. They are (1) the Hough voting space to locate the parameters of straight edges in the image, and (2) the Region-Bit-Map for each sub-image to identify the corresponding peaks. A careful study of the effect for the deviation of ρ{variant} which is the normal distance of an edge pixel, has also been made. A range for the increment of ρ{variant} is suggested, which can substantially improve the accuracy of the whole approach.
ISSN: 0167-8655
EISSN: 1872-7344
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