This paper describes an approach of feature extraction from range and intensity data for three-dimensional model-based target recognition systems. The range image of the object under study is acquired using a methodology based on a passive stereo-vision model. A coarse to fine strategy is used to explore the features in the images, and cepstral analyisis provides information about disparities between corresponding areas at each step. The surfaces of the 3-D target recovered from the passive stereo-vision model are represented by aspect graphs which are used in vector form as the input for a neural network classifier.
|Number of pages||6|
|Journal||Proceedings of SPIE - The International Society for Optical Engineering|
|State||Published - Dec 1 1991|
|Event||Applications of Digital Image Processing XIV 1991 - San Diego, United States|
Duration: Jul 21 1991 → …