A method for recognition, such as classification and/or localisation of three dimensional objects, said one or more objects being imaged so as to provide a recognition image being a two dimensional digital image of the object, said method utilises a database in which numerical descriptors are stored for a number of training images, the numerical descriptors are the intrinsic and extrinsic properties of a feature, said method comprising: - identifying features, being predefined sets of at least two primitives, and determining contours for the image, where the primitives are determined by the steps: - generating gradients of the digital image, - finding one or more local maxima of the absolute gradients, - use the one or more local maxima as seeds for generating contours, the generation of the contours for each seed comprising determining an ordered list of points representing positions in the digital image and belonging to a contour, - for all of said positions determining the curvature of the contours; - from the determined curvatures determine primitives as characteristic points on or segments of the contours, - extracting numerical descriptors of the features, said numerical descriptors being of the two kind: - extrinsic properties of the feature, wherein the extrinsic properties comprises a reference point of the feature and a reference direction, and - rotation invariant intrinsic properties of the feature, where - the intrinsic properties and the reference direction are derived after a tilt-pan homographic transformation has been applied to the feature, said transformation moving the reference point to the mid-image point of the recognition image, where the tilt-pan homographic transformation comprises successive camera rotations by a virtual camera about an axis parallel to an horizontal image axis and about an axis parallel to a vertical image axis, - matching said properties with those stored in the database and in case a match is found assign the object corresponding to the properties matched in the database to be similar to the object of the object to be recognised. - identifying features, being predefined sets of at least two primitives, and determining contours for the image, where the primitives are determined by the steps: - generating gradients of the digital image, - finding one or more local maxima of the absolute gradients, - use the one or more local maxima as seeds for generating contours, the generation of the contours for each seed comprising determining an ordered list of points representing positions in the digital image and belonging to a contour, - for all of said positions determining the curvature of the contours; - from the determined curvatures determine primitives as characteristic points on or segments of the contours, - generating gradients of the digital image, - finding one or more local maxima of the absolute gradients, - use the one or more local maxima as seeds for generating contours, the generation of the contours for each seed comprising determining an ordered list of points representing positions in the digital image and belonging to a contour, - for all of said positions determining the curvature of the contours; - from the determined curvatures determine primitives as characteristic points on or segments of the contours, - extracting numerical descriptors of the features, said numerical descriptors being of the two kind: - extrinsic properties of the feature, wherein the extrinsic properties comprises a reference point of the feature and a reference direction, and - rotation invariant intrinsic properties of the feature, where - extrinsic properties of the feature, wherein the extrinsic properties comprises a reference point of the feature and a reference direction, and - rotation invariant intrinsic properties of the feature, where - the intrinsic properties and the reference direction are derived after a tilt-pan homographic transformation has been applied to the feature, said transformation moving the reference point to the mid-image point of the recognition image, where the tilt-pan homographic transformation comprises successive camera rotations by a virtual camera about an axis parallel to an horizontal image axis and about an axis parallel to a vertical image axis, - matching said properties with those stored in the database and in case a match is found assign the object corresponding to the properties matched in the database to be similar to the object of the object to be recognised.