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FPGA Implementation of Multi-scale Pedestrian Detection in Thermal Images

References [1] Bailey, D.G. (2011). Design for embedded image processing on FPGAs. John Wiley & Sons. [2] Benenson, R., Omran, M., Hosang, J., Schiele, B. (2014, September). Ten years of pedestrian detection, what have we learned?. In European Conference on Computer Vision (pp. 613-627). Springer International Publishing [3] Bulat, B., Kryjak, T., Gorgon, M. (2014, September). Implementation of advanced foreground segmentation algorithms gmm, vibe and pbas in fpga and gpu-a comparison. In International Conference on Computer Vision and

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Digital processing methods of images and signals in electromagnetic infiltration process

References [1] I. Kubiak, A. Przybysz, S. Musial, K. Grzesiak, Raster Generator in the Electromagnetic Infiltration Process, Military University of Technology, 2012 [2] R.G. Lyons, Understanding Digital Signal Processing (2nd Edition), 2004 [3] T. Zielinski, Digital Signal Processing, Communication and Transport Publisher, 2009 [4] D.J. Park, K.M. Nam, Multiresolution Edge Detection Techniques, Patern Recognition, Vol. 28, 1995 [5] K. Pratt, Digital Image Processing,Wiley and Sons

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Usage of Digital Image Correlation in Analysis of Cracking Processes

. Manner - Correlation analysis on GPU systems using NVIDIA’s CUDA. Journal of Real-Time Image Processing. Volume 6 Issue 4, December 2011, 275-280 [7] Kirk, W. Hwu - Programming Massively Parallel Processors a Hands-on Approach. Elsevier 2010. ISBN: 978-0-12-381472-2

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Analysis of the Granular Material Concentration Changes During Silo Discharging Process Based on X-Ray Image Analysis

thesis, Department of Physics University of Bergen [10] Grudzien, K. (2012). Radiography Image Processing for Analysis of Gravitational Funnel Flow in Silo, Computer Science in Novel Applications, 137-158 [11] Grudzien, K., Gonzales, M. (2013). Detection of tracer particles in tomography images foranalysis of gravitational flow in silo, Image Processing and Communications, 18, 11-22 [12] Grudzien, K., Niedostatkiewicz, M., Jerome, A., Maire, E., Babout, L. (2012). Analysis of the bulk solid flow during gravitational silo

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Industrial Applications of Image Processing

annual IEEE Conference on Automation Science and Engineering (IEEE CASE 2009), 8,p. 158-163 Chattopadhyay, T, et al. (2008). An Application for Retrieval of Frames from a Laparoscopic Surgical Video Based on Image of Query Instrument. TENCON 2008, IEEE Region 10 Conference, 11, p. 1-5 Chattopadhyay, T. (2012) Applications of Image Processing in Industries, CSI Communications, July 2012, p. 8-11 Davies, E.R. (2012) Computer and Machine Vision, 4th Edition: Theory, Algorithms, Practicalities Golnabi, H

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The Use of Image Processing Methods to Improve the Detection of User’s Hand in Vision Based Games Used in Neurological Rehabilitation

. [4] Burke, J.W., Morrow, P.J., McNeill, M.D.J., Mc-Donough, S.M., Charles, D.K. (2008). Vision based games for upper-limb stroke rehabilitation. In Machine Vision and Image Processing Conference , 2008. IMVIP’08. International (pp. 159-164). IEEE [5] Burke, J.W., McNeill, M.D.J., Charles, D.K., Morrow, P.J., Crosbie, J.H., McDonough, S.M. (2010). Designing engaging, playable games for rehabilitation. In Proceedings of the 8th International Conference on Disability, Virtual Reality & Associated Technologies (pp. 195-201) [6] Cameirao, M.S., i Badia, S

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Parametric logarithmic type image processing for contrast based auto-focus in extreme lighting conditions

References Byrski, W. and Byrski, J. (2012). The role of parameter constraints in EE and OE methods for optimal identification of continuous LTI models, International Journal of Applied Mathematics and Computer Science 22 (2): 379-388, DOI: 10.2478/v10006-012-0028-3. Deng, G. (2009). An entropy interpretation of the logarithmic image processing model with application to contrast enhancement, IEEE Transactions on Image Processing 18 (5): 1135-1140. Deng, G. (2012). A generalized logarithmic image

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Map Merging in the Context of Image Processing

, M. Gini "Merging Partial Maps Without Using Odometry," in Multi-Robot Systems. From Swarms to Intelligent Automata , III vol., Netherlands: Springer, 2005, pp. 133-144. K. Ho and P. Newman "Multiple Map Intersection Detection using Visual Appearance," in 3rd International Conference on Computational Intelligence , Singapore, 2005 J. Bernd Digital Image Processing. 5 th Edition , Springer-Verlag, 2002 B. Zitova and J. Flusser "Image registration methods: a survey,"in Image and vision

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Remarks on Hardware Implementation of Image Processing Algorithms

References Drzazga A., Hajdul J., Malec J. and Wnuk M. (1983). Hardware image preprocessor, Technical Report , Wrocław University of Technology (in Polish). Dudani S., Breeding K. and McGhee R. (1977). Aircraft identification by moment invariants, IEEE Transactions on Computers , 26 (1): 39-46. SGS-THOMSON Microelectronics (1994). IMSA110 Image and Signal Processing Sub-system Texas Instruments Europe (1997

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Image Processing for Technological Diagnostics of Metallurgical Facilities

References 1. Akovetsky, V. I. Deciphering Pictures. Moscow, Nedra, 1983 (in Russian). 2. Aleksandrov, V. V., N. D. Gorsky. Image Presentation and Processing. A Recursive Approach. Moscow, Nauka, 1985 (in Russian). 3. Digital Coding TV Images. I. I. Tsukerman, Ed., Moscow, Svyaz, 1981 (in Russian). 4. Krasilnikov, N. N. Theory of Transmission and Reception of Images. Moscow, Radio and Svyaz, 1986 (in Russian). 5. Jahne, B. Digital Image Processing. Berlin, Springer Verlag

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