Using Extension Theory to Design a Low-Cost and High-Accurate Personal Recognition System

With the advancement in information technology, personal recognition systems have attracted wide attention. With more options of the recognition systems, the recognition rate and price become very important. This paper used palmprint with the extension method to design a low-cost personal recognition system. First, this paper uses a low-cost webcam to capture the image of palmprints, here the length, slop, and distance of principal line of palmprints can be captured by the image process method. Generally, the devices for capturing hand images should have higher-resolution, so their prices are higher. This paper used a low-pixel and low-cost webcam as the capturer, and it had also a high recognition rate that is equivalent in high resolution devices. The recognition algorithm of this study used extension algorithm for hand recognition and was compared with other traditional algorithms and recognition systems. Finally, the experimental results showed that the method proposed in this study has higher recognition rate than traditional algorithms and proved that low-resolution and low-cost capture tools have a high recognition rate as well.