This paper describes an automatic method for recognizing wild flowers. Recognition requires two pictures, a frontal flower image and a leaf image taken by a digital camera. Seventeen (17) features, eight from the flower and nine from the leaf, are fed to a neural network. We collected 20 pairs of pictures from 16 wild flowers in the fields around our campus. We obtained a recognition rate of 95% with all the 17 features. Then we investigated which features are more effective for recognition and found that four features of flowers and two features of leaves can yield the best accuracy of 96%.