A target recognition method based on local fuzzy thresholds is presented to solve the problems of serious background interference, the absence of reference map for complex terrain objects and the low contrast between the target and the background. Firstly, a multi-threshold algorithm is designed and a saliency map is produced based on the establishment of multi-scale space. Then, the Itti model is improved and a candidate target filtering model is constructed by using the local fuzzy threshold method based on an image fuzzy rate. Finally, the detected results are precisely matched using Integral Nprod to determine the right one. The experimental results indicate that the match rate of the algorithm has increased nearly by 20% and 40% and the time consumption by 75% and 50% as compared with those of Hausdorff distance algorithm and Integral Nprod algorithm, respectively.In conclusions, the new algorithm has the advantages of high match rate, high speed and high accuracy for FLIR targets in complicated backgrounds.