Method for automatically detecting ambiguities in a matrix of a first 2D structure for a matching method for determining the optical flow in order to estimate or to detect the motion of pixels, comprising the following steps: - providing a matrix of a first 2D structure having matrix elements by means of a first processing unit, wherein the first 2D structure is an image provided by a camera sensor, and the matrix is an image excerpt from the first 2D structure, wherein the matrix element corresponds to a pixel and its position in an image excerpt and the value of the matrix element represents a feature of the pixel, wherein such a feature is a grey scale value or a colour value or a complex value that can comprise the surroundings of a pixel and/or neighbourhood relationships with other pixels; - providing a comparison matrix of a second 2D structure having comparison matrix elements by means of a second processing unit, wherein the comparison matrix is a comparison image from the second 2D structure, wherein said second 2D structure is likewise an image from the camera sensor, and the comparison image is larger than or equal to the image excerpt, wherein the comparison matrix corresponds to an image region, determined at a time different from that pertaining to the image of the first 2D structure, - comparing the matrix with the comparison matrix by means of a comparison algorithm in a comparator unit; wherein the image excerpt to be compared and the comparison image are each transformed pixel by pixel with a binary descriptor, wherein the comparison algorithm is a Hamming distance function which pixel by pixel maps the distances of the binary descriptors to scalar similarity values, wherein the steps (S100 to S300) are part of the matching method, and - forming a similarity matrix having similarity elements from the results of the comparison; wherein the similarity values are summed over the image excerpt and are stored in the similarity matrix having similarity elements, wherein the similarity matrix constitutes an intermediate step of the matching method, - evaluating the similarity matrix in an evaluation unit by means of an evaluation function along a path which includes a plurality of similarity elements, wherein the evaluation function calculates the positive differences of neighbouring similarity elements and sums them, wherein the sum formed thereby is a measure of the ambiguity present in the matrix, and - generating an evaluation result as a measure of an ambiguity present in the matrix of the first 2D structure, wherein, if the evaluation result indicates with respect to a region as an ambiguity measure a period or an edge in the first camera image or the matrix, the optical flow vector in this region is discarded. - providing a matrix of a first 2D structure having matrix elements by means of a first processing unit, wherein the first 2D structure is an image provided by a camera sensor, and the matrix is an image excerpt from the first 2D structure, wherein the matrix element corresponds to a pixel and its position in an image excerpt and the value of the matrix element represents a feature of the pixel, wherein such a feature is a grey scale value or a colour value or a complex value that can comprise the surroundings of a pixel and/or neighbourhood relationships with other pixels; - providing a comparison matrix of a second 2D structure having comparison matrix elements by means of a second processing unit, wherein the comparison matrix is a comparison image from the second 2D structure, wherein said second 2D structure is likewise an image from the camera sensor, and the comparison image is larger than or equal to the image excerpt, wherein the comparison matrix corresponds to an image region, determined at a time different from that pertaining to the image of the first 2D structure, - comparing the matrix with the comparison matrix by means of a comparison algorithm in a comparator unit; wherein the image excerpt to be compared and the comparison image are each transformed pixel by pixel with a binary descriptor, wherein the comparison algorithm is a Hamming distance function which pixel by pixel maps the distances of the binary descriptors to scalar similarity values, wherein the steps (S100 to S300) are part of the matching method, and - forming a similarity matrix having similarity elements from the results of the comparison; wherein the similarity values are summed over the image excerpt and are stored in the similarity matrix having similarity elements, wherein the similarity matrix constitutes an intermediate step of the matching method, - evaluating the similarity matrix in an evaluation unit by means of an evaluation function along a path which includes a plurality of similarity elements, wherein the evaluation function calculates the positive differences of neighbouring similarity elements and sums them, wherein the sum formed thereby is a measure of the ambiguity present in the matrix, and - generating an evaluation result as a measure of an ambiguity present in the matrix of the first 2D structure, wherein, if the evaluation result indicates with respect to a region as an ambiguity measure a period or an edge in the first camera image or the matrix, the optical flow vector in this region is discarded.