Abstract: A method for detecting road lane markings for a motor vehicle in motion with an image recording unit is presented. The image recording unit points to the road in front of the vehicle and in the recorded image data, brightness differences (contrasts) are analysed and/or edges are extracted. Road lane markings are detected by means of their periodic arrangement. For evaluation purposes, the measuring signal of the image recording unit is transformed into another coordinate system, and the auxiliary function thus obtained is tested for periodic structures.

Abstract: An image processing method for detecting the activation of brake lights of vehicles driving in front, which do not emit an additional or a changed modulated signal during the braking procedure, has been presented. For this purpose, an image sensor or an image sensor system is aligned to a point in front of the vehicle, the camera images are fed into a memory and a motor vehicle driving in front is identified by means of a pattern recognition method on the image; in addition, following the detection of the vehicle, image areas are determined which contain brake lights to a high degree of probability.

Abstract: The invention relates to a method for determining a speed of a vehicle (1), whereby at least two images (A, B) of an area surrounding the vehicle are recorded in time succession using a camera on the vehicle (1), and between the images (A, B) changes (2) in a position and/or a size of at least one object (X) contained in the images (X) are determined, and from the changes, a speed of the vehicle (1) is determined relative to the object (X)

Abstract: In the inventive process the morphological characteristics of point-shaped vehicle lane markers are evaluated on the basis of a priori knowledge. For this, those estimation processes are particularly useful, which are based on a Kalman Filter. After the selection of suitable ROI a Matched Filter is employed, in order to better extract from the background the image points associated with a vehicle lane marker. The inventive process is obviously not limited to point-shaped vehicle lane markers.

Abstract: Image data of optically acquired input images (1) are processed for emphasizing at least two object classes. Each pixel is subjected to a rough classification (10) based on first criteria that determine whether or not a pixel is relevant for an object recognition. A reduced image (11) is formed from the relevant pixels and irrelevant pixels are omitted. The reduced image (11) is filtered (20) for forming at least two correlated filtered images (21, 22, 23) based on second criteria. Classified images (31A, 32A, 33A) are formed from the filtered images by classifiers that work in accordance with predetermined rules. Weighting factors are allocated to each object class. The classified images are merged in accordance with an algorithm to make a combined global evaluation for each object class. The global evaluation decides, based on the merged images (41A, 41B, 41C), for each pixel whether the respective pixel belongs to an object class and if so to which object class.

Abstract: A method for the detection of helicopters from a flying platform utilizes an imaging sensor. Relevant image regions of two successive images are subtracted from one another with respect to picture elements, and within the thus formed differential image, segments are identified by means of a threshold value process. Straight lines of the same orientation are adapted to the identified segments, and intersection points are determined for all such straight lines. Identification of a helicopter is made based on a bunching of the intersection points.

Abstract: A method for the detection of helicopters from a flying platform utilizes an imaging sensor. Relevant image regions of two successive images are subtracted from one another with respect to picture elements, and within the thus formed differential image, segments are identified by means of a threshold value process. Straight lines of the same orientation are adapted to the identified segments, and intersection points are determined for all such straight lines. Identification of a helicopter is made based on a bunching of the intersection points.

Abstract: A method for the detection of helicopters from a flying platform utilizes an imaging sensor. Relevant image regions of two successive images are subtracted from one another with respect to picture elements, and within the thus formed differential image, segments are identified by means of a threshold value process. Straight lines of the same orientation are adapted to the identified segments, and intersection points are determined for all such straight lines. Identification of a helicopter is made based on a bunching of the intersection points.

Abstract: A process for recognizing the course of the road ahead for a motor vehicle shall be provided, in which the velocity of the vehicle is determined and the position and the velocity of objects located ahead are determined by rigid search antennas oriented in the direction of travel via a radar sensor system, and which makes possible a simple, forward-looking recognition of the course of the road by special evaluation of the measured position and velocity data available. The roadside-specific targets are filtered out of the fixed target by the threshold value comparison of the fixed target amplitudes, and the current distances between the vehicle and the side of the road are determined in discrete angle ranges by ordering filtration. The distances from the side of the road, estimated for each angle range, are sent as characteristics to a classifier for the prediction of the curve type lying ahead, and they are used as support values for a nonlinear regression to obtain a curvature parameter of the curve.