Affiliation:
1. Institute of Computer and Information Science, Faculty of Mechanical Engineering and Computer Science , Częstochowa University of Technology , 73 Dąbrowskiego Str., 42-200 Częstochowa , Poland
Abstract
Abstract
The article presents a possible way to detect key points. The tests were carried out by the case of detection of a reference object in static images. For comparative purposes, Chris Harris & Mike Stephens [11] and Speeded-Up Robust Features (SURF) detectors [2, 3] were used. The descriptors were built based on the Fast Retina Key point (FREAK) [1, 16] and SURF algorithms [2, 3]. Six different configurations of key point detection methods with the above descriptors were implemented. The obtained results have been presented on exemplary images and in the table. They show that this type of detection of an element of interest can be successful and should be developed.
Reference23 articles.
1. [1] Alahi, A., Ortiz, R., Vandergheynst, P. (2012, June). Freak: Fast retina keypoint. In Computer vision and pattern recognition (CVPR), 2012 IEEE conference on (pp. 510-517). IEEE
2. [2] Bay, H., Ess, A., Tuytelaars, T., Van Gool, L. (2008). Speeded-up robust features (SURF). Computer vision and image understanding, 110(3), 346-359
3. [3] Bay H., Tuytelaars T., Van Gool L., (2006). SURF: Speededup robust features, Lecture Notes in Computer Science, 3951, 404-417
4. [4] Choraś M., (2006). Ear biometrics: feature extraction methods based on geometrical parameters, Przegląd Elektrotechniczny, 12/2006, 5-10
5. [5] Donoser, M., Bischof, H. (2006, June). Efficient maximally stable extremal region (MSER) tracking. In Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on (Vol. 1, pp. 553-560). IEEE