RST_INVARIANT_CVIP
rst_invariant_cvip() -calculates the 7 RST-invariant features defined in Table 6.1 of reference 1.
Contents
SYNTAX
phi = rst_invariant_cvip(labeledImage, [r, c], featSelect)
Input parameter include:
- labelImage - Label image of MxN size with single object or multiple objects. Each object has unique gray value.
- r - The row number of a pixel on the object. positive integer.
- c - The column number of a pixel on the object. positive integer.
- featSelect - The features that are needed to be calculated out of the available 7-RST-invariant features.
Output parameter include :
- phi - The 7 RST-invariant features in a row vector.
DESCRIPTION
This function calculates the RST-invariant features of a binary object in a labeled image specified by the row and column coordinates given as inputs by the user. The user should also specify the features that are to be calculated.
REFERENCE
1.Scott E Umbaugh. DIGITAL IMAGE PROCESSING AND ANALYSIS: Applications with MATLAB and CVIPtools, 3rd Edition.
EXAMPLE
% Read Image input_img = imread('Shapes.bmp'); lab_image = label_cvip(input_img); % Calling function phi = rst_invariant_cvip(lab_image, [140, 119],[1 0 0 1 1 1 1]) % (391,139) is a pixel on the bottom ellipse phi = rst_invariant_cvip(lab_image, [262, 97],[1 1 1 1 1 1 1]) % (391,139) is a pixel on the bottom ellipse % Display input image figure; imshow(input_img,[]);title('input image');
phi =
'row_obj' 'col_obj' 'rst1' 'rst4' 'rst5' 'rst6' 'rst7'
[ 140] [ 119] [0.1592] [ 0] [ 0] [ 0] [ 0]
phi =
Columns 1 through 7
'row_obj' 'col_obj' 'rst1' 'rst2' 'rst3' 'rst4' 'rst5'
[ 262] [ 97] [0.1592] [ 0] [ 0] [ 0] [ 0]
Columns 8 through 9
'rst6' 'rst7'
[ 0] [ 0]
CREDITS
Author: Mehrdad Alvandipour, March 2017
Copyright © 2017-2018 Scott
E Umbaugh
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