掌纹识别　the palmprint feature extraction and classification tasks

mainly to complete the palmprint feature extraction and classification tasks. The data set contains 99 people's palm print pictures, in which 3 palm print pictures of each person are distributed in the training set, and the other 3 palm print pictures are distributed in the test set. In this project, I tried the traditional method use SIFT to extract features and KNN for classification which get accuracy of 97.31%, and also tried the convolutional neural network method such as ResNet which get a