Research of shoeprint image stream retrival algorithm with scale-invariance feature transform

Shoeprints left at the crime scene provide valuable information to criminal investigation due to distinctive patterns in the sole. Those shoeprints are often incomplete and noise ones because incomplete and noise prints may be resulted from external destruction or incomplete contact between shoe sole and the ground surface. In this study a method including feature extraction of keypoints and similarity matching is proposed for recognition and retrieval of partial and noise shoeprint images. Experimental results show the full-size prints and toe prints perform best among all shoeprints. Furthermore, this system also demonstrates its robustness against noise because there is a very slight difference in comparison between original shoeprints and noise shoeprints.