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Retrieval of Relevant Visual Data in Selected Machine Vision Tasks: Examples of Hardware-based and Software-based Solutions

Authors: Andrzej Śluzek


To illustrate diversity of methods used to extract relevant (where the concept of relevance can be differently defined for different applications) visual data, the paper discusses three groups of such methods. They have been selected from a range of alternatives to highlight how hardware and software tools can be complementarily used in order to achieve various functionalities in case of different specifications of “relevant data". First, principles of gated imaging are presented (where relevance is determined by the range). The second methodology is intended for intelligent intrusion detection, while the last one is used for content-based image matching and retrieval. All methods have been developed within projects supervised by the author.

Keywords: Relevant visual data, gated imaging, intrusion detection, image matching.

Digital Object Identifier (DOI):

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[1] A. W. Ellis and A. W. Young, Human Cognitive Neuropsychology. Hove: Psychology Press, 1996, ch. 2 & ch. 3.
[2] R. Lepage, "Data reduction in machine vision and remote sensing applications," in Proc. Int. Conf. Information and Communication Technologies: From Theory to Applications, Damascus, 2004, pp: LXIII-LXIV.
[3] A.N. Belbachir (ed.), Smart Cameras. Springer Verlag, 2009.
[4] G.R. Fournier, D. Bonnier, J.L. Forand and P.W. Pace, "Range gated underwater laser imaging system," Optical Engineering , vol. 32, pp. 2185-2190, 1993.
[5] C.S. Tan, A. Sluzek and G. Seet, "Model of gated imaging in turbid medium," Optical Engineering, vol. 44, no. 11, 2005, pp. 116002-1-8.
[6] A. Sluzek, H. Fujishima and C.S. Tan, "Real-time digital control in gated imaging," in: Proc. 5th EURASIP Conf. on Speech and Image Processing, Multimedia Communication & Services, Smolenice (Slovakia), 2005, pp. 201-206.
[7] A. Sluzek, A. Palaniappan, "Development of a reconfigurable sensor network for intrusion detection," in Proc. 2005 MAPLD Int. Conf. on Military and Aerospace Applications of Programmable Logic Devices, Washington D.C., 2005
[8] M.K. Hu, "Visual pattern recognition by moment invariants," IRE Trans. Inf. Theory, vol.8, 1962, pp 179-187.
[9] S. Maitra, "Moment invariants," Proc. of IEEE, vol. 67, no. 4, 1979, pp. 697-699.
[10] K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. Van Gool, "A comparison of affine region detectors," Int. Journal of Computer Vision, vol. 65, 2005, pp 43- 72.
[11] K. Mikolajczyk, C. Schmid, "A performance evaluation of local descriptors." IEEE Trans. PAMI, vol. 27, 2005, pp 1615-1630.
[12] F.L. Bookstein, "Principle warps: thin plate splines and the decomposition of deformations." IEEE Trans. PAMI, vol. 16, 1989, pp 460-468.
[13] D.D. Yang and A. Sluzek, "Aligned matching: an efficient image matching technique," in: Proc. IEEE Conf. Image Proc ICIP 2009, Cairo - to be published.
[14] R.O. Duda and P.E. Hart, "Use of the Hough transformation to detect lines and curves in pictures," Comm. ACM, vol. 15, 1972, pp 11-15.
[15] A. Sluzek, "Images features based on local Hough transforms," Lecture Notes on AI, vol. 5712, 2009, pp 143-150.
[16] E.D. Sinzinger, "Amodel-based approach to junction detection using radial energy," Pattern Recognition, vol. 41, 2008, 494-505.
[17] D.D. Yang and A. Sluzek, "Performance improvement of SIFT descriptor by using linear discriminant analysis," unpublished.