1. A method for identifying keypoints in a digital image comprising a set of pixels, each pixel having associated thereto a respective value of an image representative parameter, said method comprising: approximating a filtered image, said filtered image depending on a filtering parameter and comprising for each pixel of the image a filtering function that depends on the filtering parameter to calculate a filtered value of the value of the representative parameter of the pixel, said approximating comprising: a) generating a set of base filtered images, each base filtered image being the image filtered with a respective value of the filtering parameter; b) for each pixel of at least a subset of said set of pixels, approximating the filtering function based on a respective approximation function based on the base filtered images, said approximation function being a function of the filtering parameter within a predefined range of the filtering parameter; for each pixel of said subset, identifying such pixel as a candidate keypoint if the approximation function has a local extreme which is also a global extreme with respect to the filtering parameter in a respective sub-range within said predefined range, the sub-range being less than the predefined range; for each pixel identified as a candidate keypoint: c) comparing the value assumed by the approximation function at the value of the filtering parameter corresponding to the global extreme of the pixel with the values assumed by the approximation functions of the adjacent pixels in the image at the values of the filtering parameters of the respective global extremes of such adjacent pixels, and d) selecting such pixel based on this comparison, wherein said filtered image is based on filtering said digital image with a filtering function that is based on a Gaussian function having a filtering parameter that is the standard deviation of the Gaussian function.