For big noises tire image, a method of character truncation was presented to get distinguishing outer contourfeatures. Artificial neural network and features of relations was used to recognize tire specifications. First, the samplefeatures of distinguishing specifications were gotten: two-thirds characters were intercepted to get run-lengthcharacteristics of its external contour. Then, one recognition result was gotten by BP neural network training andrecognition. Finally, character features of relations processed fore results were applied to do the second recognition.Experimental results show that the characteristics of acquisition and the second recognition algorithms can effectivelyidentify the tire specifications. Moreover, BP neural network has better fault-tolerance and recognition rate fordeformation characters caused by noises, and feature gotten and secondary identification algorithm can effectivelyidentify tire specifications.