H = VL_HARRIS(I,SI) computes the Harris corner strength of the image I at ``integration'' scale SI.
The Harris strength  of a pixel is a statistic of the gradient of the image integrated in a neighborhood of that pixel. This neighborhood is a Gaussian window of variance SI.
In computing the Harris corner strength, there is a second scale parameter, the ``derivation'' scale SD, which is the variance of the Gaussian kernel used to pre-smooth the image I before computing its gradient. SI and SD are independent parameters and VL_HARRIS(I,SI) assumes that I is already smoothed at level SD.
VL_HARRIS(I,SI) uses Noble's variation  of the Harris score. If SIGMAP and SIGMAM are respectively the biggest and smallest eigenvalue of the structure tensor at a pixel, the score is given by (SIGMAP*SIGMAM) / (SIGMAP+SIGMAM/2). Let GAMMA = SIGMAM/SIGMAP the ratio between the eigenvalues, which measures the degree of anisotropy of the tensor and is always comprised in the range [0,1]. Noble's score can be decomposed in two factors: the biggest eigenvalue SIGMAP and the number
RHO = (2 GAMMA) / (GAMMA + 1).
RHO is another measure of isotropy that has value one for a symmetric tensor and and zero for maximally anisotropic tensor. [H,DETAILS] = VL_HARRIS(I,SIGMA) returns the additional structure DETAILS with the following fields:
VL_HARRIS(I,SI,ALPHA) uses Harris' original score , defined to be SIGMAP*SIGMAM - ALPHA*(SIGMAP+SIGMAM)^2. This can be decomposed in the factors SIGMAP^2 (note the square) and
RHO = GAMMA - ALPHA (1+GAMMA)^2.
Note that RHO is equal to -ALPHA for a maximally anisotropic tensor. Typically ALPHA=0.04 and this is what is used by VL_HARRIS(I,SI,).
REMARK. The gradient of the image I, used to compute the structure tensor, is computed using central differencies. This means that a function line [+1,-1,+1,...] has null Harris' score. This is generally assumed to be a sampling artifact, and might be avoided by oversampling the image.
To extacts Harris points from image I:
idx = vl_localmax( vl_harris( vl_imsmooth( I, sd ), si ) ) ; [i,j] = ind2sub( size(I), idx )
 C. Harris and M. Stephens, "A combined corner and edge detector," in Proceedings of The Fourth Alvey Vision Conference, pp. 147-151, 1988.
 J. A. Noble, "Finding corners, "Image Vision Computing, vol. 6, no. 2, pp. 121-128, 1988.
See also: VL_HELP().