Detect features from an image with SIFT algorithm
fobj = imdetect_SIFT(im [,nfeatures [,nOctaveLayers [,contrastThreshold [,edgeThreshold [,sigma]]]]])
Input image
The number of best features to retain. The features are ranked by their scores. Default value is 0.
The number of layers in each octave. Default value is 3.
The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. Default value is 0.04.
The threshold used to filter out edge-like features. Default value is 10.
The sigma of the Gaussian applied to the input image at the octave #0. Default value is 1.6.
Features object contains following fields -
Type of features
Numbers of detected features
Coordinates of the detected features - X
Coordinates of the detected features - Y
Size of detected features
keypoint orientation
The response by which the most strong keypoints have been selected.
pyramid octave in which the keypoint has been detected
object id
This function used to detect the features of an image using SIFT method
1. OpenCV 2.4 Online Documentation