1. A method for a case-based recognition of HEp-2 cells in digital images of HEp-2 cell sections, comprising: acquiring data for each image by manual tracing of edges of an image in the form of visible outer and/or inner contours of HEp-2 cells by means of a hand-held input device connected to a computer, wherein the data can be correlated with these edges and the HEp-2 cells as objects represented thereby; eliminating a translation of each object such that each object is moved into the origin of a coordinate system; scaling each object in accordance with the correlated data within the coordinate system; comparing at least two objects with one another, respectively, wherein the objects are oriented toward one another, wherein for comparing scaling and/or rotation is carried out; calculating at the same time a similarity based on D ⁡ ( P , O ) = ∑ i = 1 N ⁢ ⁢  ( p i - μ p ) δ p - R ⁡ ( Θ ) ⁢ ( o i - μ o ) δ o  2 P, O—objects Θ—rotation matrix μ p and μ o —center points of the objects P and O δ p and δ o —the sums of the squared spacings of each point from the center points; during calculation of the similarity, determining similarity parameters either as distance values or similarity values between the objects, respectively, until either a minimum of the distance values or a maximum of the similarity values is present; based on the determined distance values or similarity values, forming sets of similar objects and hierarchically ordering the sets as a dendogram; and dividing the dendogram by presetting distance values or similarity values into groups and selecting within the groups one prototype, respectively, wherein the prototype either is an averaged shape averaged based on individual shapes of the group or the median of the group of the individual shapes.