Fast accurate contours for 3D shape recognition

We describe an efficient GPU algorithm which extracts multiple contours from an image. The algorithm uses crack codes to generate contours which sit logically between adjacent image values; it works scan line by scan line and it can generate multiple contours in parallel with an image streamed directly from a camera. Whilst specifically targeted at detecting object contours in stereo disparity maps, it can also be used for general segmentation with a trivial change to the code generating the crack code masks. Using a480 ALU 1.4 GHz nVidia GPU, it can generate ~ 25000 contours from a real 2048 × 768 resolution 128 level disparity map image in ~ 29 ms if the contours are further processed in the GPU (additional ~5 ms to calculate shape moments) or ~ 39 ms if contours are transferred to the host. This is ~ 40 times faster than an OpenCV CPU implementation.