Commonly Visual Servoing is separated into tracking and control parts. None of the previous methods attempt to optimize these two parts. In Kernel Base Visual Servoing method the main purpose is to combine and optimize whole control loop. By kernel definition a lyapanov candidate function is formed and control input is computed to proof the lyapanove stability. It is implemented in four degrees of freedom. In this thesis previous algorithm is implemented and also a new method in scale and rotation correction is presented. We propose Log-Polar Transform instead of Fourier Transform for 2 degrees of freedom. Besides we synthesize all four degrees of freedom to show visual tracking. Comparison between LPT and FFT shows advantages of our new method.