A Basic Introduction to OpenCV for Image Processing.pdf

A Basic Introduction to OpenCV for Image Processing Qing Chen (David) E-mail: qchen@discover.uottawa.ca DiscoverLab School of Information Technology Engineering University of Ottawa January 15, 2007 2Outline 1. Introduction 2. Image data structure in OpenCV 3. Basic operations for images 4. Working with videos 5. References and resources 31. Introduction General description Open source computer vision library in C/C++. Optimized and intended for real-time applications. OS/hardware/window-manager independent. Generic image/video loading, saving, and acquisition. Both low and high level API. Provides interface to Intels Integrated Performance Primitives (IPP) with processor specific optimization (Intel processors). 41. Introduction Features: Image data manipulation (allocation, release, copying, setting, conversion). Image and video I/O (file and camera based input, image/video file output). Matrix and vector manipulation and linear algebra routines. Various dynamic data structures (lists, queues, sets, trees, graphs). Basic image processing (filtering, edge detection, corner detection, sampling and interpolation, color conversion, morphological operations, histograms, image pyramids). Structural analysis (connected components, contour processing, distance transform, various moments, template matching, Hough transform, polygonal approximation, line fitting, ellipse fitting, Delaunay triangulation). Camera calibration (finding and tracking calibration patterns, calibration, fundamental matrix estimation, homography estimation, stereo correspondence). Motion analysis (optical flow, motion segmentation, tracking). Object recognition (eigen-methods, HMM). Basic GUI (display image/video, keyboard and mouse handling, scroll-bars). Image labeling (line, conic, polygon, text drawing). 51. Introduction OpenCV modules: cv - Main OpenCV functions. cvaux - Auxiliary (experimental) OpenCV functions. cxcore - Data structures and linear algebra suppor