Sliding Window Filters and Edge Detection.ppt

Sliding Window Filters and Edge Detection Longin Jan Latecki Computer Graphics and Image Processing CIS 601 – Fall 2004 Binary Case Black pixels have value 0 White (background pixels) have value 1 Edge Detection What are edges in an image? Edges are those places in an image that correspond to object boundaries. Edges are pixels where image brightness changes abruptly. More About Edges An edge is a property attached to an individual pixel and is calculated from the image function behavior in a neighborhood of the pixel. It is a vector variable (magnitude of the gradient, direction of an edge) . Image To Edge Map Edge Detection Edge information in an image is found by looking at the relationship a pixel has with its neighborhoods. If a pixel’s gray-level value is similar to those around it, there is probably not an edge at that point. If a pixel’s has neighbors with widely varying gray levels, it may present an edge point. Edge Detection Methods Many are implemented with convolution mask and based on discrete approximations to differential operators. Differential operations measure the rate of change in the image brightness function. Some operators return orientation information. Other only return information about the existence of an edge at each point. Roberts Operator Mark edge point only No information about edge orientation Work best with binary images Primary disadvantage: High sensitivity to noise Few pixels are used to approximate the gradient Roberts Operator (Cont.) First form of Roberts Operator Second form of Roberts Operator Prewitt Operator Looks for edges in both horizontal and vertical directions, then combine the information into a single metric. Edge Magnitude = Edge Direction = Sobel Operator Similar to the Prewitt, with different mask coefficients: Edge Magnitude = Edge Direction = Kirsch Compass Masks Taking a single mask and rotating it to 8 major compass orientations: N, NW, W, SW, S, SE, E, and NE.