Intelligence image fusion recognition algorithm based on Dempster-Shafer evidence reasoning

Three dimension object recognition is a basic problem of computer vision field. There were uncertainness, uncompleteness and unclarity in acquirement data as invariant moment theory was applied to recognize three dimension image target, therefore recognition efficiency could not meet the needs of actual system. By combining Dempster-Shafer evidence reasoning with invariant moment theory, intelligence image fusion recognition algorithm was present. A basic belief assignment function was constructed, and a classify rule was built. Dempster combination rule and the absorptive method were used for recognizing three dimension airplane image. The result of simulation indicated that absorptive method had higher recognition efficiency than Dempster combination rule.

[1]  R. Wong,et al.  Scene matching with invariant moments , 1978 .

[2]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[3]  Robert B. McGhee,et al.  Aircraft Identification by Moment Invariants , 1977, IEEE Transactions on Computers.

[4]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[5]  Bjørnar Tessem,et al.  Approximations for Efficient Computation in the Theory of Evidence , 1993, Artif. Intell..