Active contours or snakes are computer-generated curves that move within images to find object boundaries. They are often used in computer vision and image analysis to detect and locate objects and to describe their shape. For example, a snake could be used for edge detection, corner detection, motion detection, and stereo matching; one could be used to find the outline of an organ in a medical image; or one could be used to automatically identify characters on a postal letter. The active contour model, also called snakes, is a structure in computer vision for delineating the contour of an object from a possibly noisy 2D image. The snake model is popular in computer vision, and snakes are widely used in applications such as object tracking, shape recognition, segmentation, edge detection, and stereo matching. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get Original Essay A snake is a deformable, energy-minimizing spline, influenced by image constraints and forces that pull it toward object boundaries and by internal forces that resist deformation. Snakes can be understood as a special case of the general technique of matching a deformable pattern to an image via energy minimization. In two dimensions, the active shape model represents a discrete version of this approach, leveraging the point distribution model to limit the range of shapes to an explicit domain learned from a training set. An additional force to the external force of the active contour GVF The model is called the new active contour model. This force acts as a pressure force that pushes the contour towards the boundary of the object. Without this pressing force, even if we have perfect edge detection, the curve will shrink and vanish. This new active contour model allows it to move in both directions, expanding and contracting, which makes it suitable for various image segmentation applications, including iris segmentation. Keep in mind: This is just an example. Get a custom paper from our expert writers now. Get a Custom Essay The new active contour model achieves robust and accurate iris segmentation with high recognition rates for iris images where both the pupil and iris appear non-circular and there are numerous eyelash occlusions and eyelids. iris segmentation is performed by a new active contour model after implementation of SFTA feature extraction and ANN classification techniques, the scheme is discussed below.