Neural network approach to object recognition and image partitioning within a resolution hierarchy

Joachim Utans; Gene R. Gindi

doi:10.1117/12.140000

16 September 1992 Neural network approach to object recognition and image partitioning within a resolution hierarchy

Joachim Utans, Gene R. Gindi

Proceedings Volume 1709, Applications of Artificial Neural Networks III; (1992) https://doi.org/10.1117/12.140000
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

Object recognition is a complex task involving simultaneous problems in grouping, segmentation, and matching. Previous work involved an objective function formulation of the problem, resulting in a uniform method of addressing problems in object recognition that have heretofore been approached by heterogenous complex vision systems. The complexity of our objective functions resulted in numerous optimization failures, not unexpectedly. Here we propose to prime the system with estimates of the objects parameters at a coarse, more abstract, scale. We discuss how this might be done. These initial values are expected to bring the state of the system closer to good minima.

Citation Download Citation

Joachim Utans and Gene R. Gindi "Neural network approach to object recognition and image partitioning within a resolution hierarchy", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.140000

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