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| author | shamikam | 2017-01-16 02:56:17 +0530 |
|---|---|---|
| committer | shamikam | 2017-01-16 02:56:17 +0530 |
| commit | a6df67e8bcd5159cde27556f4f6a315f8dc2215f (patch) | |
| tree | e806e966b06a53388fb300d89534354b222c2cad /macros/detectBRISKFeatures.sci | |
| download | FOSSEE_Image_Processing_Toolbox-master.tar.gz FOSSEE_Image_Processing_Toolbox-master.tar.bz2 FOSSEE_Image_Processing_Toolbox-master.zip | |
Diffstat (limited to 'macros/detectBRISKFeatures.sci')
| -rw-r--r-- | macros/detectBRISKFeatures.sci | 47 |
1 files changed, 47 insertions, 0 deletions
diff --git a/macros/detectBRISKFeatures.sci b/macros/detectBRISKFeatures.sci new file mode 100644 index 0000000..4449727 --- /dev/null +++ b/macros/detectBRISKFeatures.sci @@ -0,0 +1,47 @@ +function [varargout] = detectBRISKFeatures(image, varargin) +// This function is used to detect BRISK(Binary Robust Invariant Scalable Keypoints) Features in a grayscale Image. +// +// Calling Sequence +// result = detectBRISKFeatures(Image); +// result = detectBRISKFeatures(Image, Name, Value, ...) +// +// Parameters +// result: BRISKPoints 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. +// MinContrast : (Optional) The minimum difference in intensity between a corner and its surrounding region. (Default: 0.2). The value must be between 0 and 1. +// NumOctaves : (Optional)The number of Octaves that the detector uses. (Default - 3) The value must be an integer scalar in between 1 and 4. +// MinQuality : (Optional) This specifies the minimum quality accepted for corners. (Default - 0.1) The value must be between 0 and 1. +// 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 returns the BRISK features detected in a 2D grayscale image. +// +// Examples +// image = imread('sample.jpg'); +// results = detectBRISKFeatures(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("Too many output arguments")) + end + select rhs + case 1 then + [a b c d e]= ocv_detectBRISKFeatures(image_list) + case 3 then + [a b c d e]= ocv_detectBRISKFeatures(image_list, varargin(1), varargin(2)) + case 5 then + [a b c d e]= ocv_detectBRISKFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4)) + case 7 then + [a b c d e]= ocv_detectBRISKFeatures(image_list, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6)) + case 9 then + [a b c d e]= ocv_detectBRISKFeatures(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 ,'Scale', d, 'Count', e); +endfunction |