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Acknowledgments. The work was co-financed by The Polish National Centre for Research and Development (NCBR), as a part of the EUREKA Project №. C 2012/1-5 MITSU. References 1. : The efficient real- and non-real-time make and model recognition of cars. Multimedia Tools Appl. 74(12), 4269–4288 (2015). 1007/s11042-013-1545-2 2. : Video artifacts assessment for live mobile streaming applications. , Curado, M. ) FMN 2009. LNCS, vol. 5630, pp. 242–247. Springer, Heidelberg (2009) 3. : Very high accuracy velocity estimation using orientation tensors, parametric motion and simultaneous segmentation of motion field.

116, 408) .. 255 [256]G (502, 990) In Table 3 are presented results of the mapping method for Lena image pixels. , 256. In the third column, the EC mapped points are resulted for all image pixels values with successful iteration of k. To encrypt the EC mapped points resulted from Table 3, we utilize EC-points sequence generated from C-D ECPRNG. In this case, we choose the same generator point G = (502, 23) and initial value U0 = (4, 386) belong to E defined in (11) and the random bits bi generated from the Logistic map defined in Sect.

Signal processing used to implement a VAD algorithm is described in this first section. In the second section, the part of the metric regarding video is exposed. The combination of techniques used to detect the movement of the lips are explained. In the third and last section, the algorithm that compares the audio and visual information between each other is described. Every section includes a results subsection and a further research subsection too that will complete the approach to the method developed to detect the delay between a visual media and an audio media.

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A Hacker's Revenge

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