PPT-Canny Edge Detection Using an NVIDIA GPU and CUDA

Alex Wade CAP6938 Final Project Introduction GPU based implementation of A Computational Approach to Edge Detection by John Canny Paper presents an accurate localized edge detection method Purpose. CUDA Platform. CUDA Parallel Computing Platform. . Hardware . . . Capabilities. GPUDirect. SMX. Dynamic Parallelism. HyperQ. Programming . Approaches. Libraries. “Drop-in” Acceleration. Author: Michael Sedivy. Introduction. Edge Detection in Image Processing. MCMC and the Use of Gibbs Sampler. Input. Results. Conclusion/Future Work. References. Edge Detection. Detecting Edges in images is a complex task, but it useful in other image processing problems. CSE . 576. Ali Farhadi. Many slides from Steve Seitz and Larry . Zitnick. Edge. Attneave's. Cat (1954) . Edges are caused by a variety of factors. depth discontinuity. surface color discontinuity. illumination discontinuity. Winter in . Kraków. photographed by . Marcin. . Ryczek. Edge detection. Goal: . Identify sudden changes (discontinuities) in an image. Intuitively, most semantic and shape information from the image can be encoded in the edges. . Edge Detection. Consider this picture. We would like its output to be. Concepts: Review. Weighted sum. Convolution . Gradients. Vector (of gradients). Magnitude of a vector (of gradients). Algorithms for edge detection: Review. Alex Wade. CAP6938 Final Project. Introduction. GPU based implementation of . A Computational Approach to Edge Detection. by John Canny. Paper presents an accurate, localized edge detection method. Purpose. . Szymon Rusinkiewicz. Convolution: . how to derive discrete 2D convolution. 1-dimensional. 2-dimensional. Discrete. Where f(i,j) is any given image, g(i,j) is a mask, . h(i,j) is an new image obtained.. Vinay B Gavirangaswamy. Canny edge detection algorithm. Output. Original. Single Threaded. Output (contd.). Original . Multi-Threaded (. OpenMP. ). Output (contd.). Original. Multi-Threaded. (GPU-CUDA). heterogeneous programming. Brian Gregor. bgregor@bu.edu. Research Computing Services. Boston University. CUDA C/C BASICS. NVIDIA . Corporation. © NVIDIA 2013. What is CUDA?. CUDA Architecture. Expose GPU parallelism for general-purpose computing. Waters. Introduction to GPU Computing. Brief History of GPU Computing. Technical Issues. Social Impact. Marketing and Ethical . Issues. Project Management. Conclusion. Table of Contents. A . GPU is . CUDA NEW FEATURES AND UPDATES 2 ANNOUNCING CUDA 10.2 Download today at: https://developer.nvidia.com/cuda - downloads Plus Compiler, Tools and Library Enhancements & Performance Improvements See Relea hindcast . results and its preliminary evaluation in the South China Sea. Shihe Ren. a. , Xueming Zhu. a. , and Drevillon Marie. b. a. . National Marine Environmental Forcasting Center, Beijing, China. Edge. Attneave's. Cat (1954) . 2. Edges are caused by a variety of . factors.. depth discontinuity. surface color discontinuity. illumination discontinuity. surface normal discontinuity. Origin of edges. . Edge Detection. Consider this picture. We would like its output to be. So, to repeat: The purpose of Edge Detection is to find jumps in the brightness function (of an image) and mark them. . Before we get into details, we need to detour.