Segmentation of range images using morphological operations: review and examples
Linda A. Gee, Mongi A. Abidi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
Image segmentation involves calculating the position of object boundaries. For scene analysis, the intent is to differentiate objects from clutter by means of preprocessing. The object of this paper is to examine and discuss two morphological techniques for preprocessing and segmenting range images. A Morphological Watershed Algorithm has been studied in detail for segmenting range images. This algorithm uses a unique approach for defining the boundaries of objects from a morphological gradient. Several sets of range images are used as input to the algorithm to demonstrate the flexibility of the watershed technique and the experimental results support this approach as an effective method for segmenting range images. Morphological image operators present another means for segmenting range images. In particular, the results from implementing gray-scale morphological techniques indicate that these operators are useful for segmentation. This is made possible by converting a range image of a scene to a gray-scale image representation. The result represents the umbra of the surface of the objects within the scene. By applying morphological operations to the gray values of the image, the operations are applied to the umbra. Each pixel represents a point of the object's umbra, thereby yielding scene segmentation. The techniques that are discussed are found to be useful for preprocessing and segmenting range images which are direct extensions to object recognition, scene analysis, and image understanding.