A comparative study of various techniques of image segmentation for the identification of hand gesture used to guide the slide show navigation

Interaction between human and computer is becoming powerful day by day with the development of ubiquitous computing. Hand gesture recognition plays an efficient role to establish interaction between human and computer. Gesture is way of communication to understand body language. We can interact with computer using various devices like keyboard, mouse etc. This paper focus on comparing the different segmentation technique used to enhance the controling of slide show navigation without using these devices like mouse, keyboard, touch screen or laser device etc. Hand gesture recognition used to perform interaction by capturing the image, the image segmentation techniques detect the region of interst(ROI) which show the hand region. The gesture can be detected by analysing segmented hand region. All segemented regions are compared on the basis of their features. This paper show comparison of thresholding, laplacian kernel, k-means and canny edge detection segmentation technique use for recognition system to makes interaction easy, convenient and does not require any other system.