The Comparison of Template Matching and SURF for Logo Classification on Product
Thummarat Boonrod, Chatklaw Jareanpon, Phatthanaphong Chomphuwiset · 2015
This paper proposes the fast logo classification on product. The search space for logo classification is reduced by production using Histogram of Oriented Gradients (HOG). The template matching and Speeded-Up Robust Features (SURF) algorithm are used to detect the logo, and in term of the computational time. The experimental results found that the HOG can be detected the area and product at 88.00% accuracy rate. The logo detection found that the advantage of template matching is simple, but the advantage of SURF algorithm is speed.