Hand gesture is very popular and powerful form of input nowadays. Using hand gestures as an input device will be easy and convenient way of interaction between the system and human and does not require any extra input device. The project is a desktop application developed in Python using Flash Framework which uses various image processing techniques. The purpose of this project is to be able to use various hand gestures as a means of input for media player control. For this process, Motion and contour feature detection technique is used to continuously monitor the video taken from the webcam for the hand gestures and obtaining the number of fingers present in the gesture and perform the corresponding control events associated with the particular gesture. Moreover, Haar Cascade classifiers are used for face and eye detection, which does not allow the user to miss parts of the video when he/she moves away from the screen. The project can be implemented to effectively control the media player using hand gestures and view media content without missing any parts of it. This efficiency of the project can be further enhanced by using machine learning or machine training for more accurate hand gesture recognition.