Abstract: A method of detecting motion is described. A first image is captured and exposed by a digital camera. The first image information is transferred to a control device. Gray level values of a specific group in the first image are then stored. Real-time gray level values corresponding to the specific group in a real time image are subsequently captured. The real-time gray level values of the specific group in a real time image are compared with the gray level values of the specific group in the first image. An amount of specific points with different gray level between the specific groups in the real-time image and the first image greater than N indicates an object of the real-time image is in motion or else the object of the real-time image is motionless. A sequential step for the object detected to be in motion is then performed. The real-time gray level values of the specific group in the real-time image are stored as the gray level values of the specific group in the first image.

Abstract: A method of detecting motion is described. A first image is captured and exposed by a digital camera. The first image information is transferred to a control device. Gray level values of a specific group in the first image are then stored. Real-time gray level values corresponding to the specific group in a real time image are subsequently captured. The real-time gray level values of the specific group in a real time image are compared with the gray level values of the specific group in the first image. An amount of specific points with different gray level between the specific groups in the real-time image and the first image greater than N indicates an object of the real-time image is in motion or else the object of the real-time image is motionless, A sequential step for the object detected to be in motion is then performed. The real-time gray level values of the specific group in the real-time image are stored as the gray level values of the specific group in the first image.