Research of Image Processing Algorithm Based on Region of Interest

Article Preview

Abstract:

With the further development of modern scientific study, it promotes the research of the image based on region of interest. By doing these studies, it satisfies the pressing needs in many fields such as military, production and living areas, etc. meanwhile, it is also the key problem in the fields of computer vision, image processing, artificial intelligence, video communication. Visual attention plays a very important role in the human information processing of the psychological adjustment mechanism. It is a conscious activity which chooses the useful information from large amounts of information. It owns the high efficiency and reliability in the process of human visual perception. Visual attention model, which is based on the visual attention and combined with the computer vision, builds a spatial feature of visual attention architecture. It is helpful not only to find out the visual cognition rule, but also to solve the problem of interested area selection and focus on improving the efficiency of the computer image processing. It has important application value in areas such as image extraction and image zooming. The paper has carried out the deeply study in the interested image region. With the improved visual attention model as a starting point, it combines with graph processing algorithm. And it uses the image extraction algorithm and image zooming algorithm to improve the visual attention model and detect the interested area.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 798-799)

Pages:

814-817

Citation:

Online since:

September 2013

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] C.M. Privitera, L. W. Stark. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(9): 970-982.

Google Scholar

[2] D. LaBerge, & M. Carter, V. Brown. Neural Computation, 1992, 4(3): 318-331.

Google Scholar

[3] D. LaBerge. Consciousness and Cognition, 1997, 6(2): 149-181.

Google Scholar

[4] R. Desimone & J. Duncan. Annual Review of Neuroscience, 1995, 18(1): 193-222.

Google Scholar