Abstract: A detection system implemented in a vehicle to detect free parking space is disclosed. The system comprises an input unit for imaging perspective view around the vehicle and a processing unit to receive a sequence of images from the at least one image sensor and detect at least one polygon pertaining to a parking slot in at least one image of the sequence of images, transform the at least one image into a bird's-eye-view image using a homography matrix, detect at least one quadrilateral pertaining to a parking slot, transform the bird's-eye-view image comprising the at least one quadrilateral, into corresponding image pertaining to perspective view around the vehicle using an inverse homography matrix, to analyse real world co-ordinates of the parking slot, and determine type of the parking slot by computing real world dimensions based on analysis of the real world co-ordinates of the parking slot.

Abstract: A detection system implemented in a vehicle to detect free parking space is disclosed. The system comprises an input unit for imaging perspective view around the vehicle and a processing unit to receive a sequence of images from the at least one image sensor and detect at least one polygon pertaining to a parking slot in at least one image of the sequence of images, transform the at least one image into a bird's-eye-view image using a homography matrix, detect at least one quadrilateral pertaining to a parking slot, transform the bird's-eye-view image comprising the at least one quadrilateral, into corresponding image pertaining to perspective view around the vehicle using an inverse homography matrix, to analyse real world co-ordinates of the parking slot, and determine type of the parking slot by computing real world dimensions based on analysis of the real world co-ordinates of the parking slot.

Abstract: Systems and methods for lane detection that are capable of providing a warning to a driver of a vehicle in case the vehicle deviates from the detected lane. The method includes receiving a plurality of images captured by an image capturing device, pre-processing the received plurality of images to obtain a Region of Interest (RoI) in the plurality of images, and obtain one or more edge features over the RoI, extracting one or more ridge features based on processing of the RoI, detecting an indication of a footpoint of one or more probable lane lines based on the extracted ridge features, detecting a potential lane based on the footpoint of the probable lane lines, applying a mask on the one or more edge features to obtain relevant edges, and detecting a final lane based on the extracted relevant edges and based on the footpoint of the probable lane lines.

Abstract: A night-time rear collision warning system that includes a camera and a controller. The system identifies a bright spot corresponding to a light source present in the field of view of the camera, determines if the bright spot corresponds to headlights of an approaching vehicle, and determines if a collision is likely. The headlights of a distant approaching vehicle may appear as a single bright spot and so the bright spot is classified as a fused spot. By analyzing bright spots from headlights, the system is able to operate at night when no other information regarding the size or shape of the approaching vehicle is available.

Abstract: Bright spots imaged by a forward-looking monochrome video camera during night-time operation of a host vehicle are detected and classified to determine the presence of leading and on-coming vehicles. A specified region-of-interest in each image frame is globally scanned to adaptively detect the bright spot contours, and search windows bounding the larger bright spot contours are locally scanned to adaptively detect individual bright spot contours that were fused in the global scan. A sensitive area within the region-of-interest is locally scanned to adaptively detect dim taillights of a leading vehicle, and path prediction of the host vehicle is used for frame-to-frame tracking of detected spots. Detected spots are classified depending on their location and frame-to-frame movement within the region-of-interest and their glare and pairing characteristics.

Abstract: Bright spots imaged by a forward-looking monochrome video camera during night-time operation of a host vehicle are detected and classified to determine the presence of leading and on-coming vehicles. A specified region-of-interest in each image frame is globally scanned to adaptively detect the bright spot contours, and search windows bounding the larger bright spot contours are locally scanned to adaptively detect individual bright spot contours that were fused in the global scan. A sensitive area within the region-of-interest is locally scanned to adaptively detect dim taillights of a leading vehicle, and path prediction of the host vehicle is used for frame-to-frame tracking of detected spots. Detected spots are classified depending on their location and frame-to-frame movement within the region-of-interest and their glare and pairing characteristics.