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Novel visual object descriptor using surf and clustering algorithms

Grycuk R.

Journal of Applied Mathematics and Computational Mechanics

2016

Vol. 15, nr 3

37--46

In this paper we propose a method for object description based on two wellknown clustering algorithms (k-means and mean shift) and the SURF method for keypoints detection. We also perform a comparison of these clustering methods in object description area. Both of these algorithms require one input parameter; k-means (k, number of objects) and mean shift (h, window). Our approach is suitable for images with a non-homogeneous background thus, the algorithm can be used not only on trivial images. In the future we will try to remove non-important keypoints detected by the SURF algorithm. Our method is a part of a larger CBIR system and it is used as a preprocessing stage.

New image descriptor from edge detector and blob extractor

Grycuk R., Scherer R., Gabryel M.

Journal of Applied Mathematics and Computational Mechanics

2015

Vol. 14, nr 4

31--39

In this paper we present a novel approach for image description. The method is based on two well-known algorithms: edge detection and blob extraction. In the edge detection step we use the Canny detector. Our method provides a mathematical description of each object in the input image. On the output of the presented algorithm we obtain a histogram, which can be used in various fields of computer vision. In this paper we applied it in the content-based image retrieval system. The simulations proved the effectiveness of our method.

A note on Töeplitz matrix-based model in biometrics

Saeed K.

Journal of Medical Informatics & Technologies

2008

Vol. 12

29--31

This paper presents a summary of the work presented as an invited paper at MIT 2008 International Conference. The work comprises a general note on the problems we meet in our everyday contact with biometrics and their different systems. A particular attention is paid to the anti-spoofing approaches in having a safe and convenient system of human verification for personal identification. A conclusion is drawn that neither stand-alone nor multi-system Biometrics are ideal and convenient to people for their daily necessity of being identified. The author suggests a system that may seem practical in banks and cash machines, for example, in which a biometric system is used (fingerprint or face identification for example) in conjunction with the popular means of account securing, the PIN code.