Abstract: This disclosure relates generally to lane detection, and more particularly to method and systems for lane detection. In one embodiment, a method for lane detection is includes generating an edge image including inbound edges of lane-markings corresponding to a road image. Based on an adaptive thresholding of intensity of lane-markings from image strips selected from the image, a plurality of lane masks are extracted. A plurality of valid lane masks are selected from the plurality of lane masks based on a structure and intensity information of the plurality of valid lane masks in the image strips. An overlap between the inbound edges and the valid lane masks is determined to identify a plurality of edge segments of the pair of inbound edges belonging to the lane-markings. A set of valid edge segments of the pair of inbound edges are obtained based on the curvature information of the edge segments.

Abstract: A computer implemented system and method for extracting and recognizing alphanumeric characters from traffic signs is envisaged. A camera present in the system is adapted to be mounted on the vehicle for capturing images of traffic signs. The system then gives a region of interest (ROI) within the frame of the captured image, from where the alphanumeric characters are extracted and enhanced for recognition. For recognizing the enhanced alphanumeric characters, the image is converted to binary image and morphological thinning technique is applied on it. The space then obtained between two alphanumeric characters thus helps in extracting the characters and recognizing them independently from the captured image. For each extracted alphanumeric character is re-sized to a specified size and is recognized with the help of white pixels count. Once the alphanumeric characters are recognized they are displayed on a display.

Abstract: This disclosure relates generally to lane detection, and more particularly to method and systems for lane detection. In one embodiment, a method for lane detection is includes generating an edge image including inbound edges of lane-markings corresponding to a road image. Based on an adaptive thresholding of intensity of lane-markings from image strips selected from the image, a plurality of lane masks are extracted. A plurality of valid lane masks are selected from the plurality of lane masks based on a structure and intensity information of the plurality of valid lane masks in the image strips. An overlap between the inbound edges and the valid lane masks is determined to identify a plurality of edge segments of the pair of inbound edges belonging to the lane-markings. A set of valid edge segments of the pair of inbound edges are obtained based on the curvature information of the edge segments.

Abstract: A computer implemented system and method for extracting and recognizing alphanumeric characters from traffic signs is envisaged. A camera present in the system is adapted to be mounted on the vehicle for capturing images of traffic signs. The system then gives a region of interest (ROI) within the frame of the captured image, from where the alphanumeric characters are extracted and enhanced for recognition. For recognizing the enhanced alphanumeric characters, the image is converted to binary image and morphological thinning technique is applied on it. The space then obtained between two alphanumeric characters thus helps in extracting the characters and recognizing them independently from the captured image. For each extracted alphanumeric character is re-sized to a specified size and is recognized with the help of white pixels count. Once the alphanumeric characters are recognized they are displayed on a display.