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+function [varargout] = detectSURFFeatures(image, varargin)
+// This function is used to detect SURF(Speeded Up Robust Features) Features in a grayscale Image.
+//
+// Calling Sequence
+//   result = detectSURFFeatures(Image);
+//	 result = detectSURFFeatures(Image, Name, Value, ...)
+//
+// Parameters
+// result: SURFPoints struct which contains Location of KeyPoints, Orientation, Metric, SignOfLaplacian, Scale and Count of the features.
+// Image :  Input image, specified as a A-by-N 2D grayscale.
+// MetricThreshold : (Optional) With default value equal to 1000, it is to be specified as a scalar. Every interest point detected has a strength associated with it. In case, only the stronget ones are needed, this parameter has to be given a larger value. To get more no of interest points/blobs, it is to be reduced.
+// NumOctaves : (Optional)With default value equal to 3, it is to be specified as a scalar. Larger the number of octaves, larger is the size of blobs detected. This is because higher octave use large sized filters. Value must be an integer scalar in between 1 and 4.
+// NumScaleLevels : (Optional)With default value equal to 4, it is to be specified as a scalar. It denotes the number of scale level for each octave. The Value must be an integer scalar greater than or equal to 3.
+// ROI : (Optional) Region Of Interest. This is taken as a vector [u v width height]. When specified, the function detects the key points within region of area width*height with u and v being the top left corner coordinates.
+// Description
+// This function return the SURF(Speeded Up Robust Features) Interest Points for a 2D Grayscale image. It is scale- and rotation- invariant point detector and descriptor and its application include Camera Calibration, 3D Reconstruction, Object Recognition to name a few. 
+//
+// Examples
+// image = imread('sample.jpg');
+// results = detectSURFFeatures(image);
+//
+// Authors
+//  Shashank Shekhar
+	image_list = mattolist(image);	
+	[ lhs, rhs ] = argn(0)
+	if rhs > 9 then
+		error(msprintf("Too many input arguments"))
+	end	
+	if lhs > 1 then
+		error(msprintf("Not enough input arguments"))
+	end
+	select rhs 
+		case 1 then			
+			[a b c d e f] = ocv_detectSURFFeatures(image_list)		
+		case 3 then			
+			[a b c d e f] = ocv_detectSURFFeatures(image_list, varargin(1), varargin(2))			
+		case 5 then		
+			[a b c d e f] = ocv_detectSURFFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4))			
+		case 7 then	
+			[a b c d e f] = ocv_detectSURFFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6))			
+		case 9 then		
+			[a b c d e f] = ocv_detectSURFFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6), varargin(7), varargin(8))
+	end
+	varargout(1) = struct('KeyPoints', a, 'Orientation', b, 'Metric', c ,'SignOfLaplacian', d,'Scale', e, 'Count', f );
+endfunction
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