Automatic generation of image-segmentation processes

Solutions to real-world image-segmentation problems typically require many image-processing steps. Unfortunately, the user must decide how to construct this sequence of steps for a given problem. So far, no system has been proposed to make the construction of these processes "easy" for the user. As a result, segmentation processes are often laboriously developed by an image-processing expert. We describe a method for automatically generating image-segmentation processes for arbitrary images. Our method uses cue-based image analysis. The user provides problem-specific information via easily defined cues. Two types of cues can be defined: (1) iconic cues, which are image-based and constructed by drawing directly onto the image data; and (2) symbolic cues, which are verbally specified facts. The cues are interpreted to help select image-processing functions. The user need not be an image-processing expert-he must only understand the significance of the specified cues for a particular problem.