Logo detection and recognition in video stream

Logos sometimes also known as trademark have high importance in today´s marketing world. Products, companies and different gaming leagues are often recognized by their respective logos. In this paper, an implementation system for logo detection and recognition in video stream is presented. Feature set using SIFT (Scale Invariant Feature Transform) key-points is created for each query logo and the video frame being processed. The system uses a concept of bidirectional or two-way matching of features. Model fitting is carried out by using Random Sample Consensus (RANSAC) algorithm to suppress any outliers from two-way matching process. Also novel threshold scheme is used to finally make decision regarding presence of logo. Finally boundary is detected around the matched logo. The system provides various kinds of statistics like frequency of recognized logos, their visibility time and their locations in the video. Experiments were performed on various sports videos. The results of the experiments show that the developed system has achieved the precision rate of 89% and a recall of 99%.