In order to extract the text information from fuzzy inspection images efficiently and accurately,this paper proposes a combination of maximally stable extremal regions (MSER) algorithm based on edge enhancement and multi-feature adaptive weight fusion with immunogenetic (IGA) optimization support vector machine (SVM) to extract text from fuzzy inspection images.The edge-enhanced MSER algorithm is used to detect the image text,and merge the detected MSERs to get the text candidate regions.In order to filter out non-text region in the candidate regions,the feature fusion formula is used to fuse the three features of the image,then the IGA is used to optimize the SVM classifier to find the optimal parameters,and finally the candidate regions are fed into the trained classifier to filter out non-text.The experimental results show that the algorithm has higher true positive rate and lower false positive rate compared with other algorithms,higher accuracy for fuzzy inspection image text extraction.