First CommitHEADmaster

1 files changed, 57 insertions, 0 deletions

diff --git a/macros/detectMSERFeatures.sci b/macros/detectMSERFeatures.sci
new file mode 100644
index 0000000..9e1377a
--- /dev/null
+++ b/macros/detectMSERFeatures.sci
@@ -0,0 +1,57 @@
+function [regions]=detectMSERFeatures(image,varargin)
+// This function is used to detect MSER features
+//
+// Calling Sequence
+//   list_pixels = detectMSERFeatures(image, Name, Value... )
+//   [list_pixels Count Location Axes Orientation] = detectMSERFeatures(image, Name, Value... )
+//
+// Parameters
+//  Image: Input Image, should be a 2-D grayscale. The Input Image should be real
+//  ThresholdDelta [Optional Input Argument]: Step Size between intensity to be checked for measurement of stability. Values: Percentage numeric value. Default: 2.0
+//  RegionAreaRange [Optional Input Argument]: Size of the region in Pixels specified as [minArea maxArea]. Default Value: [30 14000]
+//  ROI [Optional Input Argument]: Specify a rectangular region of operation. Format [ x y width height ]. Default: [1 1 size(Image,2) size(Image,1)]
+//  MaxAreaVariation [Optional Input Argument]: Maximum Area Variation between external regions at varying thresholds for determination of stability. Values in range of (0,1]. Default 0.25
+//  list_pixels: Array of point coordinates for detected regions
+//  Location: A M-by-2 Matrix of [x y] coordinates of centroid of the ellipsoidal fit to the region
+//  Count: Count of the number of stable regions detected
+//  Axes: A M-by-2 Matrix of [majorAxis minorAxis] values for each ellipsoidal fit to the detected regions
+//  Orientation: A M-by-1 Vector containing the angle of orientation of the ellipsoidal fit in the range of [-pi/2 +pi/2] radians
+//
+// Description
+//  This function is used to detect the MSER regions, and also the corresponding ellipsoidal fit to the detected regions.
+//
+// Examples
+//   image = imread('sample.jpg');
+//   [regions] = detectMSERFeatures(image);
+//
+// With Optional Arguments:
+//   [regions location axes] = detectMSERFeatures(image, "ThresholdDelta", 10.0)
+//
+// Authors
+//  Umang Agrawal
+//  Sridhar Reddy
+
+    [lhs rhs]=argn(0);
+    if rhs>9
+        error(msprintf(" Too many input arguments"));
+    elseif modulo(rhs-1,2)<>0
+       error(msprintf("Either Argument Name or its Value missing"));
+    end
+    imageList=mattolist(image);
+    select rhs-1
+        case 0 then
+            [pixelIdxList count location axes orientation]=opencv_detectMSERFeatures(imageList);
+        case 2 then
+            [pixelIdxList count location axes orientation]=opencv_detectMSERFeatures(imageList,varargin(1),varargin(2));
+        case 4 then
+            [pixelIdxList count location axes orientation]=opencv_detectMSERFeatures(imageList,varargin(1),varargin(2),varargin(3),varargin(4));
+        case 6 then
+            [pixelIdxList count location axes orientation]=opencv_detectMSERFeatures(imageList,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5),varargin(6));
+        case 8 then
+            [pixelIdxList count location axes orientation]=opencv_detectMSERFeatures(imageList,varargin(1),varargin(2),varargin(3),varargin(4),varargin(5),varargin(6),varargin(7),varargin(8));
+    end
+    //for i=1:size(pixelIdxList)
+      //  regions(i)=struct('Count',1,'Location',location(i,:),'Axes',axes(i,:),'Orientation',orientation(i,:),'PixelIdxList',pixelIdxList(i));
+    //end
+    regions=struct('Type','MSERObject','Count',count,'Location',location,'Axes',axes,'Orientation',orientation,'PixelIdxList',pixelIdxList),
+endfunction