Skip to content

The task will deal with the area of Feature Extraction, in both the Frequency and Spatial domains

Notifications You must be signed in to change notification settings

Afreen89/Feature-Calculation

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Feature-Calculation

The task will deal with the area of Feature Extraction, in both the Frequency and Spatial domains

Task 1: spectral features

Read any image and identify spectral features for both radius and direction. I have applied FFT on the image and changed the coordinates to polar coordinates and used the radius and theta values as spectral features. To achieve this, run

Task2_part1.m

Task 2: Feature calculation

Extending task 1, I calculated first order histogram features, features from the co-occurance matrix from this paper. and five features from Gray Level Run Length(GLRL) matrix. I presented these features through various changes in bit-depth and direction.

To run the code, make sure you have these files in the same directory as your code:

chip_histogram_features.m
GLCL_Features1.m
glrlm.m

These are the built-in functions contributed by developers and are available on the functions repository of MathWorks.

Once you have these files in the same folder, run

Task2_part2.m

It contains the code for all three features to be run on an image.

Results

Here is measure of all GLRL features found using glrlm.m file. f

About

The task will deal with the area of Feature Extraction, in both the Frequency and Spatial domains

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages