Real-Time Object Detection and Recognition System Using OpenCV via SURF Algorithm in Emgu CV for Robotic Handling in Libraries

摘要

This paper describes an experimental system that has been designed, implemented and tested for object recognition and tracking in still, respectively dynamic imagessuccessive video frames captured in real time (live) with a web camera -based on Intel's open source computer vision functions library, OpenCV (Open Source Computer Vision). We propose a real-time object recognition system in intelligent library environments. The system consists of two key modules: feature extraction and object recognition. Specific detectors such as SIFT (Scale-Invariant Feature Transform) and SURF (Speeded Up Feature Robust) are efficient methods that provide high quality features, yet are too computational for use in real-time applications.