Hand gesture is one of the most important means of touchless communication between human and electronic devices. Feasibility and maintenance of hygienic standards are aspects of vision based hand gesture systems. The importance of hand gesture is to such an extent that it is predicted that the future of human-machine interaction will be based on hand gesture. There are many devices that receive their commands from hand gesture and the process of manufacturing these devices is in progress. Although hand gesture has lots of advantages over traditional means of interaction, the complexity and inaccuracy are drawbacks of these systems. Many types of research are done to cope with the weaknesses of hand gesture recognition systems but there has been no flawless solution for this system, and the improvements of these systems are still in progress. The complexity of hand gesture recognition system is highlighted when the goal is to manufacture an embedded system and a hardware implementation for this issue. Due to limitations in embedded systems designs (such as power and clock pulse constraints), designing a system with these limitations is challengeable. Few works are proposed for hand gesture recognition with hardware implementation approaches and they are mostly suffered from limitations in gesture conditions such as rotation and number of gestures. In this thesis we propose two methods for the hand gesture recognition problem. The first method is based on the hardware implementation of a well-known object detection algorithm known as Viola-Jones algorithm. We specifically concentrated on integral image generation as an important part of this algorithm. We propose a new structure of integral image which its generation is faster than the conventional method. The data size reduces as well and only a small computation load is added to the subsequent processes. To verify our work, we designe an architecture of this purpose and the comparison of speed and hardware resources are done as well. We also propose an algorithm for hand gesture recognition, which is iired by Radon transform. Due to rotation, scale and position invariance specification, Radon transform is an appropriate option for hand gesture recognition. This work detects hand angle and wrist line from projections of Radon transform. In the next step, an iired mapping of Radon transform is generated, which keeps fingers structure in the projections which are in the fingers direction. Then by performing a finger detection algorithm, the direction and position of fingers are detected. This algorithm is simple and lacks of complex calculations consist of floating point numbers. This simplicity results in hardware implementation capability. We also designe hardware architectures for implementing Radon transform and its iired mapping as the most complex parts of our algorithm. All hardware structures are designed with standard structural VHDL language and anr implemented on Xilinx Virtex6 chip. Keywords: Hand gesture, Radon transform, integral image, hardware implementation, FPGA.