The effect of noise on edge orientation computations
Pattern Recognition Letters
Precision Edge Contrast and Orientation Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparative study of Hough transform methods for circle finding
Image and Vision Computing - Special issue: 5th Alvey vision meeting
Cordic based parallel/pipelined architecture for the Hough transform
Journal of VLSI Signal Processing Systems
Efficient Algorithms for the Hough Transform on Arrays with Reconfigurable Optical Buses
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
A Parallel Pipelined Hough Transform
Euro-Par '96 Proceedings of the Second International Euro-Par Conference on Parallel Processing-Volume II
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
OpenVIDIA: parallel GPU computer vision
Proceedings of the 13th annual ACM international conference on Multimedia
Using Graphics Hardware for Enhancing Edge and Circle Detection
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Recognition of circular patterns on GPUs: Performance analysis and contributions
Journal of Parallel and Distributed Computing
High Performance Circle Detection through a GPU Rasterization Approach
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
A review of log-polar imaging for visual perception in robotics
Robotics and Autonomous Systems
Fast hough transform on GPUs: exploration of algorithm trade-offs
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
GPU accelerated image processing for lip segmentation
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part I
GPU-vote: a framework for accelerating voting algorithms on GPU
Euro-Par'12 Proceedings of the 18th international conference on Parallel Processing
Hi-index | 0.10 |
This paper presents an alternative for a fast computation of the Hough transform by taking advantage of commodity graphics processors that provide a unique combination of low cost and high performance platforms for this sort of algorithms. Optimizations focus on the features of a GPU rasterizer to evaluate, in hardware, the entire spectrum of votes for circle candidates from a small number of key points or seeds computed by the GPU vertex processor in a typical CPU manner. Number of votes and fidelity of their values are analyzed within the GPU using mathematical models as a function of the radius size for the circles to be detected and the resolution for the texture storing the results. Empirical results validate the output obtained for a much faster execution of the Circle Hough Transform (CHT): On a 1024x1024 sample image containing 20 circles of r=50 pixels, the GPU accelerates the code an order of magnitude and its rasterizer contributes with an additional 4x factor for a total speed-up greater than 40x versus a baseline CPU implementation.