1. A method for recognizing a predetermined pattern in an image data set having a number of recorded image point data, the image data set being recorded by a device for recording at least two electromagnetic frequency spectra, the method comprising the steps of: forming, by an image processor, first and second reference data vectors each having characteristic reference coefficient values for at least one of at least two pattern image points of the predetermined pattern; forming, by the image processor, a data vector having characteristic coefficient values as component for each image point of at least a selected area of the recorded image points, from the image point data of a corresponding image point and from image point data from at least one test environment of the image point, the at least one test environment consisting of image points at a predetermined distance to the corresponding image point; forming, by the image processor, at least a first difference value for the image points of the selected area as a function of a difference between the data vector of the corresponding image point and the first reference data vector; forming, by the image processor, at least a second difference value for at least one image point of the selected area as a function of a difference between the data vector of the at least one image point of the selected area image point and the second reference data vector; determining, by an image recognition processor, whether at least one pattern correlation quantity determined as a function of the first and second difference values is below a predetermined threshold value and whether the at least one pattern correlation quantity forms a local minimum in an environment of a size of a target object; recognizing, by the image recognition processor, the predetermined pattern when the at least one pattern correlation quantity is below the predetermined threshold value and the local minimum is present.