Moments in contour extraction: an algorithm and its implementation

A new methodology in contour analysis (based on the observation that image derivatives are dangerously amplifying noises) has been recently gaining popularity. Instead, contour features are directly detected from grey-level images. The paper presents a novel technique of contour feature extraction (including features more complex than usually discussed edges and corners) based on locally computed moments of intensity function. The scanning circular window is rather large (7-15 pixel radius) which allows feature extraction in noised and/or textured images. For each location of the window, a moment-based parameter fitting is used to determine the model contour feature prospectively existing at this location. Then, the model feature is matched with the actual content of the window. The results are either shown as a "feature intensity" map or can be used for further image processing. The prospects of hardware implementation are also briefly discussed.