Title :
Relaxation optimizing processes in extended probabilistic space
Author :
Horiuchi, T. ; Toraichi, K. ; Yamamoto, K. ; Yamada, H.
Author_Institution :
Inst. of Inf. Sci. & Electron., Tsukuba Univ., Ibaraki, Japan
Abstract :
Classical probabilistic relaxation method has been widely used for solving optimisation problems in various fields, including image processing and pattern recognition. However we realize that there exist cases in which a probability theoretic model is not adequate, especially there exists incompleteness in available information by noises. In order to solve the problem, this paper proposes a relaxation matching method based on Dempster-Shafer theory. Then the update process in probabilistic relaxation method is derived as a special case of Dempster´s combination rule (1967) in DS theory
Keywords :
image recognition; iterative methods; probability; Dempster-Shafer theory; extended probabilistic space; image processing; incompleteness; pattern recognition; probability theoretic model; relaxation matching method; relaxation optimizing processes; Character recognition; Dictionaries; Image processing; Ink; Integrated circuit modeling; Integrated circuit noise; Iterative methods; Nose; Pattern recognition; Relaxation methods;
Conference_Titel :
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-8186-7128-9
DOI :
10.1109/ICDAR.1995.598991
