ADVANCEMENT OF BLUR DETECTION AND SUBJECT EXTRACTION USING BACKGROUND SEQUENTIAL LEARNING AND ACTION PREDICTION TECHNOLOGY

Abstract

Author(s): T.Srilekha1, P.Preethi2, T.Pavithra3, K.Prabhu

Super-resolution technologies enable fine magnification of surveillance camera images for purposes such as face and license plate recognition. Conventional technology requires numerous extracted still images to improve the resolution of subjects in video content and enable clear subject magnification. When magnified by more than 2 or 3 times (4 to 9 times the number of pixels), however, these images become blurred. Therefore, there has been significant demand for technologies that could further improve resolution and enable greater image clarity at higher magnification. NEC's new technology creates a super-resolution image from a single extracted image (of a person's face, license plate, etc.) by utilizing a database (library) of categorized images. These images maintain fine details even when magnified by more than 4 times (more than 16 times the number of pixels), making it possible to distinguish small and distant subjects much more easily than with conventional technologies. NEC’s new technologies can be efficiently teamed with surveillance cameras to cover such large areas as airports and traffic intersections