This thesis proposes an intelligent recognition system based on neural network for hand gesture recognition. The design process is partitioned into three parts. First, the hand gesture is abstracted from an image by image procession and the characteristics of hand gesture are retrieved by the hand contour scanning method. Then, based on the back-propagation algorithm, the neural network is trained to learn the charateristics of the hand gesture. Finally, experiments are included to demonstrate the feasibility of the developed intelligent hand gesture recognition system. From the experimental results, it is clear that the system can precisely recognize the simple hand gestures related to the numbers from 1 to 5. For the more complicated case to expresss 0 to 9, the system is also available to successfully recognize all of them, after increasing the resolution of hand gesture and the number of neurons in the neural network.