with many types and variantions of existing patterns and also needs of the high recognition process becomes very important and crucial. many recognition techniques are developed to reach a similar ability with human capabilities in processing data. this paper elaborates the design of software to perform patterns recognition by using wavelet discrete transformation and fuzzy adaptive resonance theory. at the beginning, the system captures the image pattern. then, the system uses image processing techniques including wavelet discrete transformation to enhance rhe quality of the image pattern. finally, the result o information is used as an input of the fuzzy adaptive resonance theory for classifying the pattern. from the expriments , with the learning parameter value of and vigilance parameter is set to 0.87, the system reached highest accuracy of the untrained patterns recognition with 91.66% succes rate. the system also obtains a perfect match for theh trained data using the learning rate of i and various vigilance parameters.