Lections on Image analysis, OpenCV

1. Introduction. Problem of image analysis

USU / IMM Fall 2011www.uralvision.blogspot.com perevalovds@gmail.com

http://mimikirchner.com/blog/images/4:20:robots.jpg

http://s2.hubimg.com/u/1343513_f260.jpg

Introduction

At the course will be:1. Formulation and methods for analysis, processing and recognition of digital images.2. The practice of implementing algorithms in OpenCV.

Will not:1. Fundamentals of Programming C + +.2. Fundamentals of image processing in Photoshop and Gimp.3. Neural networks.

Introduction

Under Image Processing Problems we understand the problem of constructing an algorithm forAutomatic computer image analysis to extract some information from the image.

In particular, we will not consider the problems of enhancement of images for human perception.

What is an image processing problem?

Types of Image Processing Problems

Detection

Search for individual objects in the image (regions, contours), the measurement of size, etc. without specifying what they are objects.

Interpretation

Determining the type of an object in an image.

Detection

Segmentation

- Splitting the image into regions.Methods: texture analysis, contour analysis.

Motion Analysis

- Analysis of successive frames to determine the direction ofmotion of objects in the frame.Methods: The computation of optical flow.

Depth perception

- Use two cameras to estimate the distance to objects.Methods: A stereo vision.

Frame from the left cameraFrame from the right camera

The calculated map distances

Tracking objects of interest

- Calculation of the coordinates of an object on a sequence of framesMethods: Tracking.

http://www.merl.com/projects/images/particle.jpg

Branch of the object from the background- Select areas of pixels that are "objects" rather than "background"Methods: The study background for further separation, stereo vision, optical flow.

Interpretation

Recognition of object types

- Texture analysis.

Methods: The calculation of the vector of texture features and subsequent classification.

http://www.gisdevelopment.net/technology/ip/ma03029a.htm

Search for known objects

Methods: A comparison with the standard, the algorithm of Viola-Jones.

Measuring the size of the objects

Methods: A pre-calibrated camera, and then search for objects of interest and points on for size measurements.

Camera Calibration

Gesture recognition

Methods: A hidden Markov model.

http://paloma.isr.uc.pt/gesture-reco/pics/gestureLib.jpg

Orientation in space

Methods: camera calibration, the correction of perspective distortion, a comparison with the reference on the key attributes.

http://www.ics.forth.gr/ae-printerfriendly/cvrl/demos/pan_nav/pan_nav.html

Literature

Computer vision1. Gonzalez R., Woods R. Digital Image Processing.2. Shapiro, G. Stockman. "Computer vision".

OpenCV1. OpenCV C++ documentation: http://opencv.willowgarage.com/documentation/cpp/index.html

2. Gary Bradski, Adrian Kaehler,Learning OpenCV: Computer Vision with the OpenCV Library- Unfortunately, for the version of OpenCV for C, not C + +.

Philosophical Problems of recognitionM.M. Bongard, Problem of Recognition. 1967.

Homework

1. Install Visual Studio C ++ 2008 (2010) Express Edition.2. Install OpenCV 2.1 (2.2).3. Run a few examples from a folderOpenCV..\samples\c\.