Titlebook: Surfaces in Range Image Understanding; Paul J. Besl Book 1988 Springer-Verlag New York Inc. 1988 Region Growing.algorithms.differential ge

暴發(fā)戶

From Surface Labels to Surface Primitives,ange images in a general manner through surface characterization, surface segmentation, and surface matching. Although surface matching is inherently model-dependent, it was proposed that surface characterization and surface segmentation do not require knowledge of objects, only basic knowledge of s

GRUEL

Description Combination and Region Merging,t region descriptions are recorded for each region so that the effects of the sequential processing might be accounted for in the final segmentation. The static first-within-tolerance region description and the dynamic best-fit region description computed by the algorithm provide a dual region decom

oblique

Region Edges,g algorithms are not of direct concern to the digital surface segmentation algorithm, the topic of parametric edge description is of significant interest. Since the approximate shape of smooth graph surfaces in images is given parametrically by the approximating graph surface functions . = .(., .),

Ondines-curse

Experimental Results,al and noisy synthetic range images and real intensity images. These images were selected from a group of images used as a test image database for the experiments. All input images are 128×128 pixels with eight bits per pixel, except for one 256×256 8-bit intensity image of a house scene from the Un

表示向前

Conclusions and Future Directions, images can be performed without complete reliance on special purpose features by matching perceived surface descriptions with stored models of objects. In range imagery, the perceived surface descriptions directly represent scene surface geometry. In intensity imagery, geometric surface description

好忠告人

Surface Curvature Characteristics,which states that “shape perception is mediated by the detection of those geometrical properties of a figure that do not change when the figure is transformed in different ways.” Viewpoint invariance is a desirable property for any surface characteristics derived from discrete image data or from model and data surface primitive representations.

絆住

From Surface Labels to Surface Primitives, by the spatial properties of other points on the surface in small neighborhoods surrounding the given point. The key difference is that, the neighborhood of a point consists of an uncountably infinite number of points in the continuous surface case whereas a small finite number of points form the neighborhood of a digital surface point.

讓空氣進入

SLUMP

Experimental Results,ge imaging sensor into a range image using a special purpose program written by the author. All results have been obtained using software written by the author in the C programming language on the UNIX 4.2 BSD operating system running on a VAX/11–780.

Proclaim

Conclusions and Future Directions,ped into surface descriptions that have meaningful interpretations based-only on general knowledge of surfaces, this grouping process could provide an invaluable service to higher level recognition and model formation processes.