摘要：Normal 0 7.8 ? 0 2 false false false MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:????; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} A vision-based inspection method based on rough set theory, fuzzy set and BP algorithm is presented. The rough set method is used to remove redundant features for its data analysis and procession ability. The reduced data is fuzzified to represent the feature data in a more suitable form as input data of a BP network classifier. By the experimental research, the hybrid method shows good classification accuracy and short running time, which are better than the results using BP network and neural network with fuzzy input.
