Straight Line Detection AndReal -Time Line detection Using OpenGL

Line recognition is an important aspect in image processing. Many line detection algorithms were introduced. Hough Transform for line detection is difficult to accelerate using the GPU because it essentially requires rasterization of sinusoids into a highresolution raster of accumulators, which is not a suitable task for GPU. In this paper, a GPU implementation of the PClines a new parameterization of lines for the Hough Transform. PClines are a point-to-line-mapping . The detection of lines uses the graphics processor to rasterize lines into a rectangular frame buffer which is a task very natural and effective on the GPU. The OpenGL 3.3 pipeline is used to efficiently perform the whole of the PClines-based Hough Transform on the GPU. Experimental evaluation shows that even for high-resolution input images with complicated content, the line detector performs easily in real time. KeywordsLine detection, width estimation, edge, Helmholtz principle ,Acontrario detection, detection.

[1]  Pascal Monasse,et al.  Fast computation of a contrast-invariant image representation , 2000, IEEE Trans. Image Process..

[2]  B. Vainberg,et al.  On ship waves , 1993 .

[3]  Lionel Moisan,et al.  Edge Detection by Helmholtz Principle , 2001, Journal of Mathematical Imaging and Vision.

[4]  Jinhai Cai,et al.  Handwriting Recognition - Soft Computing and Probabilistic Approaches , 2003, Studies in Fuzziness and Soft Computing.

[5]  L. Moisan,et al.  Maximal meaningful events and applications to image analysis , 2003 .

[6]  P. Musé On the definition and recognition of planar shapes in digital images , 2004 .

[7]  Carsten Steger,et al.  An Unbiased Detector of Curvilinear Structures , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Azriel Rosenfeld,et al.  Picture Processing by Computer , 1969, CSUR.

[9]  Enrico Magli,et al.  On-board selection of relevant images: an application to linear feature recognition , 2001, IEEE Trans. Image Process..

[10]  Laura Igual Muñoz Image segmentation and compression using the tree of shapes of an image. Motion estimation , 2006 .

[11]  AZRIEL ROSENFELD,et al.  Digital Straight Line Segments , 1974, IEEE Transactions on Computers.

[12]  Mark J. Carlotto Enhancement of Low-Contrast Curvilinear Features in Imagery , 2007, IEEE Transactions on Image Processing.

[13]  D. Casasent,et al.  Detection of triple junction parameters in microscope images , 2001 .

[14]  Rachid Deriche,et al.  The Depth and Motion Analysis Machine , 1992, Int. J. Pattern Recognit. Artif. Intell..

[15]  David G. Lowe,et al.  Perceptual Organization and Visual Recognition , 2012 .

[16]  Guido Gerig,et al.  Multiscale detection of curvilinear structures in 2-D and 3-D image data , 1995, Proceedings of IEEE International Conference on Computer Vision.

[17]  Steven W. Zucker,et al.  Logical/Linear Operators for Image Curves , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Lionel Moisan,et al.  Meaningful Alignments , 2000, International Journal of Computer Vision.

[19]  Josiane Zerubia,et al.  Bayesian geometric model for line network extraction from satellite images , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[20]  Donald Geman,et al.  An Active Testing Model for Tracking Roads in Satellite Images , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Erkki Oja,et al.  Houghtool -- A software package for the use of the Hough transform , 1996, Pattern Recognit. Lett..

[22]  Max A. Viergever,et al.  Evaluation of Ridge Seeking Operators for Multimodality Medical Image Matching , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Rachid Deriche,et al.  Tracking line segments , 1990, Image Vis. Comput..

[24]  Michael Lindenbaum,et al.  An Integrated Model for Evaluating the Amount of Data Required for Reliable Recognition , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  J. Shaffer Multiple Hypothesis Testing , 1995 .

[26]  Chuan-Xiang Ji,et al.  Stereo match based on linear feature , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[27]  Chang-Sung Jeong,et al.  A straight line detection using principal component analysis , 2006, Pattern Recognit. Lett..

[28]  T. Viéville,et al.  Segment-based detection of moving objects in a sequence of images , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[29]  Yann Gousseau,et al.  Unsupervised thresholds for shape matching , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[30]  Josef Kittler,et al.  Hypothesis Testing: A Framework for Analyzing and Optimizing Hough Transform Performance , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Bidyut Baran Chaudhuri,et al.  A survey of Hough Transform , 2015, Pattern Recognit..

[32]  Laura Igual,et al.  Automatic low baseline stereo in urban areas , 2007 .

[33]  S. W. Thomson On Ship Waves , 1887 .

[34]  Javier Preciozzi Dense Urban Elevation Models from Stereo Images by an Affine Region Merging Approach. , 2006 .

[35]  Lionel Moisan,et al.  A Probabilistic Criterion to Detect Rigid Point Matches Between Two Images and Estimate the Fundamental Matrix , 2004, International Journal of Computer Vision.