In this document, we propose a novel palm vein recognition system using open source hardware and software. We have developed an alternative preprocessing and feature extraction technique. The proposed system is built on Raspberry Pi using OpenCV 2.4.12. The palm vein image is cropped to Region of Interest(ROI) to reduce the computational time in real time systems and then preprocessed to enhance the vein pattern visibility and to extract more number of key points using SIFT algorithm. Then the descriptors are stored in a dictionary like codebook file during training. Later the descriptors are tested with unknown patterns. The clustering is based on K-means algorithm and classification is done using Support Vector Machines (SVM).