Line positioning based on HT error compensation

The discretization of a HT space results in the ρ value detection error of a line. This paper addresses the ρ-direction precision improvement by compensating for this error. The mage are vertically or horizontally shifted, and a series peak positions are obtained by applying the standard HT (SHT) on these shifted images. The change of ρ value of a line due to these shifts is studied. On one hand this change can be measured by detecting the peak shift in HT space, on the other hand it can be obtained by geometric analysis on the vertical or horizontal shift in image space. The difference between the unit change in HT space (i.e. the ρ-direction resolution Δρ) and the unit change in image space (i.e. ρ value change due to vertical or horizontal unit shift) is used to measure the SHT ρ value detection error. A high precision ρ value is obtained by compensating for this error. The experiments show the effectiveness of the proposed method.

[1]  Hong Liu,et al.  A Nonuniform Quantization of Hough Space for the Detection of Straight Line Segments , 2007, 2007 2nd International Conference on Pervasive Computing and Applications.

[2]  Imants D. Svalbe Natural Representations for Straight Lines and the Hough Transform on Discrete Arrays , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Hans Burkhardt,et al.  Grouping edge points into line segments by sequential Hough transformation , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[4]  Dragutin Petkovic,et al.  On improving the accuracy of the Hough transform: theory, simulations, and experiments , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Vladimir Shapiro Accuracy of the straight line Hough Transform: The non-voting approach , 2006, Comput. Vis. Image Underst..

[6]  Jae Wook Jeon,et al.  An improvement of the Standard Hough Transform to detect line segments , 2008, 2008 IEEE International Conference on Industrial Technology.

[7]  Xinghui Zhang,et al.  An Improved Hough Transform Neighborhood Map for Straight Line Segments , 2010, IEEE Transactions on Image Processing.

[8]  Enrico Magli,et al.  On high resolution positioning of straight patterns via multiscale matched filtering of the Hough transform , 2001, Pattern Recognit. Lett..

[9]  Guido Gerig,et al.  LINKING IMAGE-SPACE AND ACCUMULATOR-SPACE: A NEW APPROACH FOR OBJECT-RECOGNITION. , 1987 .

[10]  Alfred M. Bruckstein,et al.  Antialiasing the Hough transform , 1991, CVGIP Graph. Model. Image Process..

[11]  Qiang Ji,et al.  Error propagation for the Hough transform , 2001, Pattern Recognit. Lett..

[12]  Adrian E. Raftery,et al.  Accurate and efficient curve detection in images: the importance sampling Hough transform , 2002, Pattern Recognit..

[13]  W. Clem Karl,et al.  Line detection in images through regularized hough transform , 2006, IEEE Transactions on Image Processing.

[14]  Joseph O'Rourke Dynamically Quantized Spaces for Focusing the Hough Transform , 1981, IJCAI.

[15]  Frans C. A. Groen,et al.  Discretization errors in the Hough transform , 1981, Pattern Recognit..

[16]  Ming Zhang On the discretization of parameter domain in Hough transformation , 1996, Proceedings of 13th International Conference on Pattern Recognition.