You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: vl_harris.m
    path of file: ./repos/robotic_perception/Trafic_Sign_Recognition/code/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox
    
    the code of the file until where you have to start completion: function [H,details] = vl_harris(I,si,alpha)
% VL_HARRIS  Harris corner strength
%  H = VL_HARRIS(I,SI) computes the Harris corner strength of the image I
%  at ``integration'' scale SI.
%
%  The Harris strength [1] 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, wh
    
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.
%
%  EXAMPLE::
%    To extacts Harris points from image I:
%      idx = vl_localmax( vl_harris( vl_imsmooth( I, sd ), si ) ) ;
%      [i,j] = ind2sub( size(I), idx )
%
%  REFERENCES::
%    [1] C. Harris and M. Stephens, "A combined corner and edge detector,"
%    in Proceedings of The Fourth Alvey Vision Conference, pp. 147-151,
%    1988.
%
%    [2] J. A. Noble, "Finding corners, "Image Vision Computing, vol. 6,
%    no. 2, pp. 121-128, 1988.
%
%  See also: VL_HELP().

% Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson.
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file).

[Ix,Iy] = gradient(I) ;
H11 = vl_imsmooth(Ix.*Ix, si) ;
H12 = vl_imsmooth(Ix.*Iy, si) ;
H22 = vl_imsmooth(Iy.*Iy, si) ;

if nargin > 2
  % Harris' original
  if isempty(alpha)
    alpha = 0.04 ;
  end