Abstract: A method for detecting damage and determining a type of damage and a degree or severity of damage to a component of a transmission. The method includes providing a first image of a portion of the component in a reference state and detecting a further image of the portion of the component after intended use. The further image of the portion of the component is detected in an installed state of the component. The method further includes determining, by comparing the further image with the first image, that the component is damaged, determining, by matching the further image against data of a damage database, a type of damage, and outputting the determined type of damage and a degree or severity of damage. The first image, the further image, and the data of the damage database are photographs.

Abstract: A device comprising a processing unit (3) configured to project at least one camera image (Img1-Img8) from at least one camera (Cam1-Cam8) onto a virtual projection surface (Proj) in order to create a virtual image (ImgV) of the vehicle interior (2).

Abstract: A method for estimating a probability distribution of the maximum coefficient of friction (?) at a current and/or future waypoint (s, s*) of a vehicle. According to the method, a first probability distribution (WV1) for the maximum coefficient of friction (?) at the waypoint (s) of the vehicle is determined by a Bayesian network from a first data set, which is, or was determined, for one, in particular current, waypoint (s) of the vehicle and which characterizes the maximum coefficient of friction (?) at the waypoint (s) of the vehicle.

Abstract: A surround view system for a vehicle, comprising a camera positioned in or on the vehicle to capture the vehicle's surroundings, an evaluation unit processing images captured by the camera and a display displaying a top-view image generated by the evaluation unit. The evaluation unit obtains the top-view image by calculating a projection of the captured images onto a virtual projection surface and by calculating a top-view of the projection on the virtual projection surface. The virtual projection surface comprises a flat bottom part and a rising part adjacent to the flat bottom part, wherein, in an area comprising the rising part at one side of the vehicle over a length of the vehicle, a curvature of the virtual projection surface is zero in a longitudinal direction of the vehicle.

Abstract: A method for detecting damage and determining a type of damage and a degree or severity of damage to a component of a transmission. The method includes providing a first image of a portion of the component in a reference state and detecting a further image of the portion of the component after intended use. The further image of the portion of the component is detected in an installed state of the component. The method further includes determining, by comparing the further image with the first image, that the component is damaged, determining, by matching the further image against data of a damage database, a type of damage, and outputting the determined type of damage and a degree or severity of damage. The first image, the further image, and the data of the damage database are photographs.

Abstract: Disclosed herein is a multi-camera driver assistance system. The system includes a plurality of cameras which dispose at different positions of a vehicle to capture images of a vicinity of the vehicle; an image processing unit which generates a virtual view with respect to a predetermined projection surface based on the images; and a display device which displays the virtual view, wherein the predetermined projection surface includes a slanted projection surfaces which are located at lateral sides of the vehicle.

Abstract: Disclosed herein is a multi-camera driver assistance system. The system includes a plurality of cameras which dispose at different positions of a vehicle to capture images of a vicinity of the vehicle; an image processing unit which generates a virtual view with respect to a predetermined projection surface based on the images; and a display device which displays the virtual view, wherein the predetermined projection surface includes a slanted projection surfaces which are located at lateral sides of the vehicle.

Abstract: Disclosed herein is a multi-camera driver assistance system. The system includes a plurality of cameras which dispose at different positions of a vehicle to capture images of a vicinity of the vehicle; an image processing unit which generates a virtual view with respect to a predetermined projection surface based on the images; and a display device which displays the virtual view, wherein the predetermined projection surface includes a slanted projection surfaces which are located at lateral sides of the vehicle.

Abstract: A method for estimating a probability distribution of the maximum coefficient of friction (?) at a current and/or future waypoint (s, s*) of a vehicle. According to the method, a first probability distribution (WV1) for the maximum coefficient of friction (?) at the waypoint (s) of the vehicle is determined by a Bayesian network from a first data set, which is, or was determined, for one, in particular current, waypoint (s) of the vehicle and which characterizes the maximum coefficient of friction (?) at the waypoint (s) of the vehicle.

Abstract: A device comprising a processing unit (3) configured to project at least one camera image (Img1-Img8) from at least one camera (Cam1-Cam8) onto a virtual projection surface (Proj) in order to create a virtual image (ImgV) of the vehicle interior (2).

Abstract: A method for determining a safe speed (v*) at a future waypoint (s*) of a vehicle moving along a route. In this step, at least one item of route data (in particular the curvature of the curve ?) characterizing the course of the route is determined. In addition, a first probability distribution (Pges) of a coefficient of friction (?) is provided at the current waypoint (s) and/or at the future waypoint (s*) of the vehicle. Subsequently a second probability distribution (Pv) of a vehicle speed (v) at the future waypoint (s*) is determined from the at least one item of route data (?) and from the first probability distribution (Pges). The safe speed (v*) is determined by statistical analysis from the second probability distribution (Pv).

Abstract: The invention relates to method of classifying an object (10) in an image (9), the method comprising the steps of: defining an image area (11) located within the object (10) in the image (9), decomposing the image area (11) into an array of subareas (13), defining an array of aggregated pixel values by calculating, for each of the subareas (13), an aggregated pixel value of the respective subarea (13), calculating a gradient array depending on differences between the aggregated pixel values of adjacent subareas (13), analyzing the gradient array, identifying, depending on a result of the analyzing step, the object (10) as belonging to a class of a predefined set of classes. Furthermore, the invention relates to a device (4) for analyzing an object (10) contained in an image (9) and to a driver assistance system as well as to a vehicle (1) containing such a device (4).

Abstract: The invention relates to method of detecting elliptical structures (10) in an image (9), comprising: detecting circular arc-shaped structures (11) in the image (9) using a circle Hough transform (CHT) of the image (9), wherein a radius and a center point (12) are determined for each circular arc-shaped structure (11), identifying pairs of circular arc-shaped structures (11) consisting of two of the detected circular arc-shaped structures (11) with substantially equal radii, defining, for each one of these pairs, a search area (14) within the image (9) depending on the center points (12) of the respective pair of circular arc-shaped structures (11), searching in the search area (14) defined for any given pair of circular arc-shaped structures (11), for a pair of edges (16) connecting these two circular arc-shaped structures (11). The invention further relates to a device for detecting elliptical structures in an image.

Abstract: The invention relates to an image processing method for automatically extracting distorted circular image elements (109; 601) from an image (101), comprising the steps of determining, by means of a circle detection (102), at least one circular image section (103; 301, 301?) as a first approximation of at least one distorted circular image element (109; 601), then determining, via a statistical color analysis of the at least one determined circular image section (301, 301?), whether the circular image section (301, 301?) belongs to one of one or more predefined color classes and, in case thereof, assigning the circular image section to the respective color class, and, finally, determining an exact shape (109; 601) of the at least one distorted circular element by starting with at least one of the one or more determined circular image sections assigned to one of the one or more color classes and varying the image section to maximize a value of a color-class specific function of the image section.

Abstract: The present invention relates to an apparatus for confirming circular traffic sign recognition including: an image acquisition unit configured to photograph a front of a vehicle using a camera to acquire a front image; a sign recognition unit configured to detect circular shapes indicating circles of objects in the front image, classify traffic sign circles indicating a traffic sign for the circles, and recognize the circular traffic sign; and a control unit configured to confirm the circular traffic sign recognition using a white inner circle and inform a driver of contents of the confirmed circular traffic sign.

Abstract: Disclosed are an apparatus and a method for detecting a bar-type sign in a traffic sign recognition system. The method may include a traffic sign detection step of detecting a traffic sign from image information including the traffic sign; a recognition region setting step of setting a recognition region on the traffic sign detected through the traffic sign detection step; a principal component analysis (PCA) operation processing step of applying a PCA algorithm to all pixels in the recognition region set through the recognition region setting step, and determining an eigenvector; and a sign determination step of determining an angle “?” of the eigenvector, comparing a deviation “d” of the determined angle with a threshold value “Pt”, and determining whether to correspond to a bar-type sign.

Abstract: Disclosed are an apparatus and a method for detecting a bar-type sign in a traffic sign recognition system. The method may include a traffic sign detection step of detecting a traffic sign from image information including the traffic sign; a recognition region setting step of setting a recognition region on the traffic sign detected through the traffic sign detection step; a principal component analysis (PCA) operation processing step of applying a PCA algorithm to all pixels in the recognition region set through the recognition region setting step, and determining an eigenvector; and a sign determination step of determining an angle “?” of the eigenvector, comparing a deviation “d” of the determined angle with a threshold value “Pt”, and determining whether to correspond to a bar-type sign.

Abstract: The present invention relates to an apparatus for confirming circular traffic sign recognition including: an image acquisition unit configured to photograph a front of a vehicle using a camera to acquire a front image; a sign recognition unit configured to detect circular shapes indicating circles of objects in the front image, classify traffic sign circles indicating a traffic sign for the circles, and recognize the circular traffic sign; and a control unit configured to confirm the circular traffic sign recognition using a white inner circle and inform a driver of contents of the confirmed circular traffic sign.

Abstract: The present invention relates to a system for detecting a region of interest about a tilted line including: an image acquisition unit configured to acquire a front image by photographing a front of a vehicle; an image processing unit configured to divide the front image in a pixel unit of a row and a column and shift the front image by one pixel in a left or right direction in each row or in an upper or lower direction in each column until a region of interest (ROI) appears in a straight line in one direction; and a control unit configured to calculate coordinate values of the pixels forming the straight line in one direction to determine the tilted line of the region of interest, when the straight line in one direction appears in the region of interest as the shifted result.

Abstract: Disclosed herein is a multi-camera driver assistance system. The system includes a plurality of cameras which dispose at different positions of a vehicle to capture images of a vicinity of the vehicle; an image processing unit which generates a virtual view with respect to a predetermined projection surface based on the images; and a display device which displays the virtual view, wherein the predetermined projection surface includes a slanted projection surfaces which are located at lateral sides of the vehicle.