A boundary-based image segmentation and representation method for binary images
David Hoy Nabors, Heggere S. Ranganath · 2000
Image processing systems have proven very useful in many space, industrial, military, and medical applications. The goal of any image processing system is to interpret a two-dimensional projection of a three-dimensional scene. Most imaging systems are composed of four stages: segmentation, region description, relational description, and interpretation. A boundary oriented segmentation method for binary images is presented in this dissertation. A curve extraction network that is capable of identifying curve segments present in binary images is described. A line detector based on two state machines that processes an extracted curve segment to output a polyline description of the input curve is also described. The curve extraction network and the state machine based line detector are suitable for hardware implementation. A graph based data structure that is compatible with the segmentation process is developed to represent objects of a digital image. The data structure used for object representation is independent of the specific object to be described. The knowledge representation scheme supports coarse/fine object matching. Scale and rotation change between input object and stored template can be easily resolved using the knowledge representation scheme. A process for identifying a complex object in an input digital image using the object template stored in the knowledge base is demonstrated.