From d17b33131c14864bd1eae275f49a3f148e21cf29 Mon Sep 17 00:00:00 2001
From: Leo Chan <leochanj@live.unc.edu>
Date: Thu, 22 Oct 2020 01:53:21 -0400
Subject: Squashed commit of the sb-vbs branch.

Includes the SD-VBS benchmarks modified to:
- Use libextra to loop as realtime jobs
- Preallocate memory before starting their main computation
- Accept input via stdin instead of via argc

Does not include the SD-VBS matlab code.

Fixes libextra execution in LITMUS^RT.
---
 SD-VBS/common/toolbox/ikkjin/harris.m | 43 +++++++++++++++++++++++++++++++++++
 1 file changed, 43 insertions(+)
 create mode 100755 SD-VBS/common/toolbox/ikkjin/harris.m

(limited to 'SD-VBS/common/toolbox/ikkjin/harris.m')

diff --git a/SD-VBS/common/toolbox/ikkjin/harris.m b/SD-VBS/common/toolbox/ikkjin/harris.m
new file mode 100755
index 0000000..92a6543
--- /dev/null
+++ b/SD-VBS/common/toolbox/ikkjin/harris.m
@@ -0,0 +1,43 @@
+
+% Sample code for detecting Harris corners, following 
+% Brown et al, CVPR 2005
+%        by Alyosha Efros, so probably buggy...
+%        slightly modified by ikkjin
+
+function [x,y,v] = harris(imrgb);
+[nr nc nb]=size(imrgb);
+if nb==3
+    im=rgb2gray(imrgb);
+else
+    im=imrgb;
+end
+
+im = im2double(im);
+g1 = fspecial('gaussian', 9,1);  % Gaussian with sigma_d 
+g2 = fspecial('gaussian', 11,1.5); % Gaussian with sigma_i 
+img1 = conv2(im,g1,'same');  % blur image with sigma_d
+Ix = conv2(img1,[-1 0 1],'same');  % take x derivative 
+Iy = conv2(img1,[-1;0;1],'same');  % take y derivative
+
+% Compute elements of the Harris matrix H
+%%% we can use blur instead of the summing window
+Ix2 = conv2(Ix.*Ix,g2,'same');
+Iy2 = conv2(Iy.*Iy,g2,'same');
+IxIy = conv2(Ix.*Iy,g2,'same');
+R = (Ix2.*Iy2 - IxIy.*IxIy) ... % det(H) 
+    ./ (Ix2 + Iy2 + eps);       % trace(H) + epsilon
+
+% don't want corners close to image border
+R([1:15, end-16:end], :) = 0;
+R(:,[1:15,end-16:end]) = 0;
+
+% non-maxima supression within 3x3 windows
+nonmax = inline('max(x)');
+Rmax = colfilt(R,[3 3],'sliding',nonmax); % find neighbrhood max
+Rnm = R.*(R == Rmax);  % supress non-max
+
+% extract all interest points
+[y,x,v] = find(Rnm);
+
+
+
-- 
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