1. An image recognition system for a vehicle comprising: at least two cameras, each camera configured to record an image of a road in the vicinity of the vehicle and to provide image data representing the respective image of the road; a first image processor configured to combine the image data provided by the at least two cameras into a first top-view image, wherein the first top-view image is aligned to a road image plane; a first feature extractor configured to extract lines from the first top-view image; a second feature extractor configured to extract an optical flow from the first top-view image and a second top-view image, which was generated before the first top-view image by the first image processor; and a kerb detector configured to detect kerbs in the road based on the extracted lines and the extracted optical flow and provide kerb data representing the detected kerbs, wherein the second feature extractor is configured to extract the optical flow as a first set of optical flow vectors, wherein the kerb detector is configured to separate the first set of optical flow vectors into a first subset of optical flow vectors and a second subset of optical flow vectors for the extended lines based on relative location between the optical flow vectors, the extracted lines, and the vehicle, wherein the kerb detector comprises a motion model calculator, which is configured to calculate at least a fitted global motion model comprising a rotation and a translation, based on the first set of optical flow vectors, and based on inline vectors of the first set of optical flow vectors, and wherein the kerb detector is configured to calculate based on the at least one fitted global motion model for every detected line a first noise distribution for the respective first subset and a second noise distribution for the respective second subset and detect a kerb at the position of the respective line if the difference between the first noise distribution and the second noise distribution exceeds a predetermined threshold.