Abstract: Disclosed is a method and video surveillance system for detecting fraud. The system may receive images. The system may convert the images into binary images. Subsequently, the system may identify a reference frame amongst the binary images. The system may trigger face detection upon detecting motion within the binary images. The system may detect the motion based on a relative white pixel count of the binary image with respect to a reference image. The system may reduce a Region of Interest (RoI) window within the binary images based on a highest density of white pixel count. The system may determine whether a face is detected within the reduced RoI window. The system may determine whether mouth is detected within a lower half of the face when the face is detected. The system may detect the fraud when the face is not detected or the mouth is not detected.

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: 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: Disclosed is a method and video surveillance system for detecting fraud. The system may receive images. The system may convert the images into binary images. Subsequently, the system may identify a reference frame amongst the binary images. The system may trigger face detection upon detecting motion within the binary images. The system may detect the motion based on a relative white pixel count of the binary image with respect to a reference image. The system may reduce a Region of Interest (RoI) window within the binary images based on a highest density of white pixel count. The system may determine whether a face is detected within the reduced RoI window. The system may determine whether mouth is detected within a lower half of the face when the face is detected. The system may detect the fraud when the face is not detected or the mouth is not detected.