Analysis and Design of Intelligent Digital Image Processing Techniques for Real Time Applications

Abstract

In recent days, capturing images with high quality and good size is so easy because of rapid improvement in quality of capturing device with less costly but superior technology. Videos are a collection of sequential images with a constant time interval. Object detection and tracking is one of the challenging task in computer vision. The existing method in this domain first tries to detect the interest object in video frames and applying in real time applications. One of the main difficulties in object tracking among many others is to choose suitable features and models for recognizing and tracking the interested object from a video. This thesis proposed various methods to solve the real time problems in the domain of Human Computer interaction and automatic face detection system. An automatic identification of various facial movements and expressions has been developed using decision-based spectral embedding and Geometric Appearance Models. A deep learning framework has been developed for facial and emotional expressions detection. A real time object detection system for smart traffic control and management using homography and digital image processing techniques has been proposed. newline