Design and Implementation of the Image Interactive System Based on Human-Computer Interaction

Abstract

Based on the traditional Human-Computer Interaction method which is mainly touch input system, the way of capturing the movement of people by using cameras is proposed. This is a convenient technique which can provide users more experience. In the article, a new way of detecting moving things is given on the basis of development of the image processing technique. The system architecture decides that the communication should be used between two different applications. After considered, named pipe is selected from many ways of communication to make sure that video is keeping in step with the movement from the analysis of the people moving. According to a large amount of data and principal knowledge, thinking of the need of actual project, a detailed system design and realization is finished. The system consists of three important modules: detecting of the people's movement, information transition between applications and video showing in step with people's movement. The article introduces the idea of each module and technique.

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S. Song, Y. Wu and F. Zhang, "Design and Implementation of the Image Interactive System Based on Human-Computer Interaction," Intelligent Information Management, Vol. 2 No. 5, 2010, pp. 334-337. doi: 10.4236/iim.2010.25040.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] R. C. Gonzalez and R. E. Woods, “Digital Image Pro- cessing,” 2nd Edition, Prentice Hall, NJ, 2002.
[2] G. Agam, “Introduction to Programming with OpenCV,” Vol. 2, 2007. http://www.cs.iit.edu/~agam/cs512/lectnotes/ opencv-intro/index.html.
[3] L. Schomaker, J. Nijtmans, A. Camurri, et al., “A Taxonomy of Multimodal Interaction in the Human Information Processing System,” Vol. 6, 1995. http://hwr. nici.kun.nl/~miami/taxonomy/taxonomy.html.
[4] C. Gu and M. C. Lee, “Semiautomatic Segmentation and Tracking of Semantic Video Objects,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 8, No. 5, 1998, pp. 572-584.
[5] W. B. Liu and B. Z. Yuan, “From Actual Reality to Virtual Reality,” Chinese Journal of Electronics, Vol. 2, 2001, pp. 100-105.
[6] J. X. Sun and D. B. Gu, “A Multiscale Edge Detection Algorithm Based on Wavelet Domain Vector Hidden Markov Tree Model,” Pattern Recognition, Vol. 37, No. 7, 2004, pp. 1315-1324.
[7] H. S. Zhu, “Communication between the Application Process and Implementation of Technology,” Computer Applications and Software, Vol. 21, No. 1, 2004, pp. 118- 120.
[8] L. Gao, Y. L. Mo and B. W. Zhu, “Adaptive Threshold Segmentation of the Image Edge Detection Method,” Computer and Communications, Vol. 25, No. 5, 2007, pp. 73-76.
[9] G. F. Yin, “Threshold Method Based on Image Segmen- tation,” Modern electronic technology, Vol. 23, 2007, pp. 107-108.
[10] C. Hui, S. He and J. L. Hu, “Video Images of Moving Target Detection,” Computer Age, Vol. 8, 2006, pp. 19- 24.
[11] G. Ge, F. H. Fan and J. X. Peng, “Background Image in the Sequence Alignment and Motion Detection Algori- thm. Data Acquisition And Processing,” Journal of Data Acquisition & Processing, Vol. 12, No. 2, 1999, pp. 164- 166.
[12] Geng for the East, L. M. Song, “Accessibility Camera- Based Interactive Techniques,” Computer Applications, Vol. 27, No. 9, 2007, pp. 2087-2090.
[13] Z. Hong, Z. H. Wang, banyan military. “Consistency of the Video Object Based on Motion Segmentation,” Naval University of Engineering, Vol. 19, No. 4, 2007, pp. 91-93, 110.
[14] N. Yao, S. T. Li and J. X. Mao, “Computer Image Processing and Recognition Technology,” Higher Educa- tion Press, 2005.
[15] J. L. Zhang and J. Liu, “Based on Wavelet and Morphology of Image Segmentation,” Chinese People's Public Security University (Natural Science), Vol. 2, 2007, pp. 65-67.

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