Detecting blur and defocusing in images is described. After detection, correction algorithms are applied. Detection provides an image processing system with parameters related to a blur (e.g., direction, strength) and noise levels, or may trigger a message to a user to re-take a photograph. Detection involves finding and analyzing edges of objects instead of an entire image. Disclosed detector may be used for OCR purposes, blur and defocusing detection in photographic and scanning devices, video cameras, print quality control systems, computer vision. Detection of blur and defocusing of an image involve second derivatives of image brightness. Object edges are detected. For points on edges, profiles of second derivative are obtained in the direction of the gradient. Statistics are gathered about parameters of profiles in various directions. By analyzing statistics, image distortions and their type (e.g., blur, defocusing), the strength of distortion, the direction of the blur are detected.