RoboCV Module 3: Delving Deeper into OpenCV

By
Mayank Prasad
President, roboVITics
VIT University, Vellore

DELVING DEEPER
INTO OPENCV
Data Types in OpenCV

Outline
2

 OpenCV Primitive Data types
 CvPoint,CvSize, CvRect, CvScalar
 Constructors of data types

 Matrix and Image Types
 CvArr,CvMat, IplImage
 CvMat Matrix Structure

 IplImage Data structure

 Matrix and Image Operators

© roboVITics | Mayank Prasad, 2012

3 OpenCV Data Types
Primitive Data Types
Matrix and Image Types
Inheritance Relationship


OpenCV Primitive Data types
4

 Several primitive data types in OpenCV
 Not present in the traditional ANSI C
 CvPoint – CvPoint2D32f, CvPoint3D32f
 CvSize, CvSize2D32f, CvRect, CvScalar


OpenCV Primitive Data types
5

 Primitive Data types are normal C structures
 Each data type has constructor method like
cvSize(), cvPoint(), cvRect()
 Since this is C, not C++, these “constructors” are
inline functions which take in list of arguments
and returns the desired data structure with
values set properly.
 CvScalar has three constructors:
cvScalar(), cvRealScalar(), cvScalarA
ll()

Matrix and Image Types
6


Inheritance Relationship
7

 Though OpenCV is programmed entirely in
C, its structures implemented can be thought to
exhibit object oriented design
 IplImage is derived from CvMat, which is in
turn derived from CvArr
 Wherever CvArr* appears in function
prototypes, it is acceptable to pass CvMat or
IplImage to the routine


8 CvMat Matrix Structure
Matrix Header
Creating, Initializing & Releasing Matrix
Accessing Matrix Data


CvMat Matrix Structure
9

 Can be created from the following definition:

 Type can be of the form:

 For example
 32bit floats CV_32FC1
 Unsigned integer 8 bit triplets CV_8UC3

 For multichannel images like RGB, operators
act on each channel separately.

CvMat Structure: Matrix Header
10

 Matrices have
 Width
 Height
 Type
 Step (length of row in
bytes)
 Pointer to data array
 And many more!!
 All members can be
accessed by de-
referencing pointers or
by calling accessory
functions


Creating Matrices
11

 Can be created in three ways:
 Create using cvCreateMat()
 Create using cvCreateMatHeader() and
cvCreateData()
 Create from an existing one by cloning it
cvCloneMat(CvMat*)
 cvCreateMatHeader() creates CvMat
structure without allocating any data
 cvCreateData() handles data allocation
 Release using cvReleaseMat(CvMat**)

Matrix Creation
12


Header Initialization
13


Header Initialization
14


Clone & Release Matrix
15


Create OpenCV Matrix
16

 Create an OpenCV Matrix with some fixed data
float vals[] = {0.8660225, -0.5000000, 0.5000000, 0.4326678};
CvMat rotmat;
cvInitMatHeader( &rotmat, 2, 2, CV_32FC1, vals );

 Simple Matrix Operations
 cvGetElemType() : Returns the type like CV_64FC4
 cvGetDims() : Returns width & height

 cvGetDimSize() : Returns the size


Accessing Matrix Data
17

 The easy way!
 The hard way!!
 The right way!!!


The Easy Way
18

 Use the CV_MAT_ELEM() macro
 Takes in the matrix, type of element to be
retrieved, row and column numbers
 Returns the desired element

 Under the hood, it calls CV_MAT_ELEM_PTR()
 Type casting is required


Why not the easy way?
19

 Re-computes pointer needed on every call
 Look up the pointer to the base element
 Calculate the offset of the desired point

 Add the offset to the base element pointer

 Easy to use, but not the best way, especially
when every element is to be accessed
sequentially


The Hard Way
20

 Easy way deals with 1D and 2D matrices
 Hard way can deal with N-dimensional matrices
 Has a lot of set/get/pointer functions
 It is a rarely used way, since many a times, vision is a
processor-intensive activity, which requires greater
efficiency
 So, do your own pointer arithmetic and de-
reference your way into the matrix
 Important in cases when an OpenCV routine is not
available for performing a particular task


The Right Way
21

 Direct access to innards of matrix
 Data storedsequentially in raster scan order
 Columns (“x”) are fastest running variable

 Channels are interleaved


The Right Way
22

 Element data is Union
 Step element can be used for offset
 Since step element is in bytes, all pointer
arithmetic is done in bytes, and later typecast
into float
 Pointer is recomputed for every row rather than
starting from the beginning


Arrays of Points
23

 Not discussed


24 IplImage Data Structure
Header Structure
Accessing Image Data
ROI and widthStep


IplImage Data Structure
25

 Similar to CvMat, but with some extra goodies
 Makes the matrix more interpretable as an
image
 This structure was originally defined as a part of
Intel’s Image Processing Library (IPL)
 It is defined as:


IplImage Header Structure
26


Depth & Channels
27

 width & height is ubiquitous
 depth & nChannels are next most crucial

 nChannels can be 1, 2, 3 or 4


Origin & Data Order
28

 origin can take two values
 Upper-left of the image, IPL_ORIGIN_TL
 Lower-left of the image, IPL_ORIGIN_BL

 dataOrder can be of two types
 IPL_DATA_ORDER_PIXEL – data packed with
multiple channels one after the other for each pixel
i.e. interleaving
 IPL_DATA_ORDER_PLANE – all the channels
clustered into image planes with planes facing each
other – not supported in OpenCV


Interleaved Images
29

Interleaving  True

Interleaving  False


Step, Data & ROI
30

 widthStep contains number of bytes between
elements of same column and successive rows
 imageData contains pointer to the first row of
the image data
 IplROI defines the practical Region of Interest
 Contains
xOffset, yOffset, height, width, coi
 COI means Channel of Interest, though not
respected by all OpenCV functions


Accessing Image Data
31

 All tasks may not have prepackaged well-
optimized subroutine in OpenCV
 So we need to access each pixel of the image
sequentially
 So, we need to handle the pointers ourselves
 widthStep can be used in bytes “as is” without
worrying because the data pointer is always of
byte type


Accessing Image Data – Example
32


ROI & widthStep
33

 ROI stands for Region Of Interest
 widthStep is the size in bytes between a pixel
and the pixel vertically below it
 In other words, widthStep refers to the size of a
row in bytes


34 Matrix & Image Operators
Different Types of Matrix Operators


Matrix & Image Operators
35

 A variety of routines are available for matrix
manipulation, most of which work equally well
for images
 They do most of the usual as well as complicated
things
 E.g.
cvAdd(), cvAddS(), cvCvtColor(), cvSe
t(), cvTranspose(), etc.


Acknowledments
36

References Image Courtesy

 Gary Bradski and  Gary Bradski and
Adrian Adrian
Kaehler, Learning Kaehler, Learning
OpenCV, O’Reilly OpenCV, O’Reilly
Media, Inc. Media, Inc.


UP NEXT
Image Processing Techniques using OpenCV

Contacts
38

 Mayank Prasad
President, roboVITics
mayank@robovitics.in
 Akshat Wahi
Asst. Project Manager, roboVITics
+91 909 250 3053
akshat@core.robovitics.in
 Akash Kashyap
President, TEC – The Electronics Club of VIT
akash130791@gmail.com


RoboCV Module 3: Delving Deeper into OpenCV

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