From c6e13c01e01f96cb721af17f13ff4714eda0bb09 Mon Sep 17 00:00:00 2001
From: MichaelK <32868357+Michael-AngeloK@users.noreply.github.com>
Date: Sat, 16 Apr 2022 17:45:19 +0200
Subject: [PATCH] Update: Added HOG feature extraction with visualization
---
Test.m | 24 +++++++++++++++++++++---
histogramGrayscale.m | 3 ++-
histogramOrientedGradients.m | 18 ++++++++++++++++++
3 files changed, 41 insertions(+), 4 deletions(-)
create mode 100644 histogramOrientedGradients.m
diff --git a/Test.m b/Test.m
index 561f022..531fef4 100644
--- a/Test.m
+++ b/Test.m
@@ -1,15 +1,33 @@
%% Example Title
% Let's use Edvard Munch's - skrik picture
-image = imread("colorHistogram/Edvard_Munch_-_Despair_(1894).jpg");
+img = imread("colorHistogram/Edvard_Munch_-_Despair_(1894).jpg");
% Let's also display the picture to see how it originally looks
%imshow(image);
%% edgeMap - Test of implementation
-edgeImage = edgeMap(image);
+%edgeImage = edgeMap(img);
-imshow(edgeImage);
+%imshow(edgeImage);
+%% HOG - Test of implementation
+% "hog" contains feature vector based on histogram of oriented gradients
+% "visual" contains visualization object that can be used in plot method
+[hog, visual] = histogramOrientedGradients(img);
+figure,
+imshow(img),
+hold on,
+plot(visual),
+title("Hog features of image");
+
+% Using Cellsize this time
+[hog2, visual2] = histogramOrientedGradients(img, 32);
+
+figure,
+imshow(img),
+hold on,
+plot(visual2),
+title("Hog features using Cellsize");
%% Section 2 Title
% Description of second code block
b = 2;
diff --git a/histogramGrayscale.m b/histogramGrayscale.m
index 45ec9c9..0f55deb 100644
--- a/histogramGrayscale.m
+++ b/histogramGrayscale.m
@@ -1,6 +1,7 @@
%Returns histogram in grayscale
function [out] = histogramGrayscale(image)
- %image ideally is already grayscaled rbg2gray() if needed
+ %Converts image into grayscale
+ image = rgb2gray(image);
[x,y] = size(image);
out = zeros(1,255);
diff --git a/histogramOrientedGradients.m b/histogramOrientedGradients.m
new file mode 100644
index 0000000..fb2b8b2
--- /dev/null
+++ b/histogramOrientedGradients.m
@@ -0,0 +1,18 @@
+% Returns histogram of oriented gradients (HOG) feauture vector of an
+% image and visualization object that can be used with plot method.
+% Useful for training a classifier.
+%
+% NB! *Requires Computer Vision Toolbox Add-on*
+%
+function [featureVector, hogVisualization] = histogramOrientedGradients(varargin)
+ if nargin==1
+ img=varargin{1};
+ [featureVector, hogVisualization] = extractHOGFeatures(img);
+ elseif nargin==2
+ img=varargin{1};
+ size=varargin{2};
+ [featureVector, hogVisualization] = extractHOGFeatures(img, "Cellsize",[size size]);
+ else
+ error('histogramOrientedGradients only accepts up to 2 input arguments!')
+ end
+end
\ No newline at end of file
--
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