1. A method for detecting edges in an image, the method comprising: smoothing the image using a filter; determining a gradient magnitude and angle for each pixel of the image; performing a non-maximum suppression; and applying a double threshold with an upper and a lower threshold for determining the edges in the image, where the upper and the lower threshold are calculated automatically using a distribution of intensity values of the image determined by using a histogram of the image divided into a predetermined number of bins; where: a normalized density function is determined for each bin resulting in a normalized probability density function, and the upper and the lower threshold are determined by using the following equations: 
 T 1 =max(0,(μ−σ)/ a ) 
 T 2 =min( A, (μ+σ)/ b ) where: μ is the mean value of the normalized probability density function, σ is the variance of the probability density function, a is a parameter, between 5 and 7, preferably 6, b is a parameter between 2 and 4, preferably 3, and A is the maximum intensity value.