DOI QR코드

DOI QR Code

Security Verification of Video Telephony System Implemented on the DM6446 DaVinci Processor

  • Received : 2012.01.11
  • Accepted : 2012.02.28
  • Published : 2012.03.28

Abstract

In this paper we propose a method for verifying video in a video telephony system implemented in DM6446 DaVinci Processor. Each frame is categorized either error free frame or error frame depending on the predefined criteria. Human face is chosen as a basic means for authenticating the video frame. Skin color based algorithm is implemented for detecting the face in the video frame. The video frame is classified as error free frame if there is single face object with clear view of facial features (eyes, nose, mouth etc.) and the background of the image frame is not different then the predefined background, otherwise it will be classified as error frame. We also implemented the image histogram based NCC (Normalized Cross Correlation) comparison for video verification to speed up the system. The experimental result shows that the system is able to classify frames with 90.83% of accuracy.

Keywords

References

  1. J. Coombs, R. Prabhu, "OpenCV on TI's $DSP+ARM{\circledR}$ Platforms: Mitigating the Challenges of Porting OpenCV to Embedded Platforms", White Paper, http://www.ti.com/lit/wp/spry175/spry175.pdf.
  2. G. Frantz, L. Adams, "DaVinciTM, Technology for Digital Video", White Paper, http://www.ti.com/lit/wp/spry067/spry067.pdf.
  3. Y-S. Jeon, M-S. Kim, Y-S. Kim, J-W. Han, "Smart Camera Hardware Design based on the TI DaVinci Processor", Int. Technical Conf. on Circuits Systems, Computers and Communications, pp. 622-624, 2009.
  4. F. Zhao, Li Yang, Y. Zhu, P. Liao, "Enhancing the Implementation of Adaboost Algorithm on a DSP-based Platform", Int. Conf. on Scalable Computing and Communications; The Eighth Int. Conf. on Embedded Computing, pp. 393-395, 2009.
  5. P. Ayyalasomayajula, S. Grassi, N. Deurin, P-A. Farine, T. Gueguen, "Implementation of an Image Recognition Algorithm on the DM6446 DaVinci Processor", Proc. of the 4th European DSP in Education and Research Conference (EDERC 2010), pp. 175-179, Dec. 1-2, 2010.
  6. Li Hua, Z. Shi-Chao, H. Chao, Z. Ming, M. Xiao-Feng, "A Near Infrared Imaging Detection System Based on DaVinci Plateform", The 9th Int. Con. on Electronics Mesurement and Instrument (ICEMI 09), pp. 154-159 Aug. 16-19, 2009.
  7. P. Han, Z. Ye, S. Yang, "The Design and Implementation of Network Video Surveillance System Based on DaVinci Chips", Advances in Information Technology and Education: Communication in Computer and Information Science, vol. 201, pp. 296-302, 2011.
  8. M.-H. Yang, D. J. Kruegman, and N. Ahuja, "Detecting Faces in Images: A Survey", IEEE Trans. on PAMI, vol. 24, pp. 34-58, Jan 2002. https://doi.org/10.1109/34.982883
  9. V. Vezhnevets, V. Sazonav, A. Andreva, "A Survey on Pixel-Based Skin Color Detection Technique", Proc. of GraphiCon, pp. 85-92, 2003.
  10. TMS320DM6446 Digital Media System-on-Chip, TI's Data Sheet, http://www.ti.com/lit/ds/sprs283h/sprs283h.pdf
  11. D. Choi, and K. N. Ngan, "Face Segmentation Using Skin-Color Map in Videophone Applications", IEEE Trans. on Circuits System and Video Telephony, Vol. 9, pp. 71-77, June 1999.