Fast Planarity Estimation and Region Growing on GPU

We present a fast approximate planarity calculation implemented on a Graphic Processing Unit (GPU). The approximate planarity of an image patch is calculated by combining the output of a number of planarity filters. We also demonstrate the use of the local planarity as a criterium for region growing. This region growing is then further optimized using a parallel implementation. The sparse nature of these filters and the inherent parallelism of the filter bank allow a fast implementation on a parallel processor architecture such as the Compute Unified Device Architecture (CUDA) from nVIDIA.

[1]  Peter Veelaert,et al.  Linear-time algorithms for region growing with applications to image and curve segmentation , 1997, Optics & Photonics.

[2]  Peter Veelaert,et al.  Geometric Constructions in the Digital Plane , 1999, Journal of Mathematical Imaging and Vision.

[3]  Alexander Zelinsky,et al.  Robust vision based lane tracking using multiple cues and particle filtering , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

[4]  Reinhard Klette,et al.  Digital planarity - A review , 2007, Discret. Appl. Math..

[5]  Jean Ponce,et al.  General Road Detection From a Single Image , 2010, IEEE Transactions on Image Processing.

[6]  Donald Scott,et al.  Shape-guided superpixel grouping for trail detection and tracking , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Christopher Rasmussen Texture-Based Vanishing Point Voting for Road Shape Estimation , 2004, BMVC.