Dynamic search of Gaussian segmentation

Shun Ido; Satoshi Arai; Ryo Takamatsu; Makoto Sato

doi:10.1117/12.251806

30 September 1996 Dynamic search of Gaussian segmentation

Shun Ido, Satoshi Arai, Ryo Takamatsu, Makoto Sato

Proceedings Volume 2826, Vision Geometry V; (1996) https://doi.org/10.1117/12.251806
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

This paper presents a new approach, called Gaussian segmentation, to extract regions containing locally concentrated stimuli. We describe two kinds of searching methods, local search and dynamic search, to link local solutions of the estimating function in parameter space in the same and different visual fields, respectively. In the local search, we propose an iterative technique which can find a local solution from any initial state of parameters by means of searching the parametric space locally. The dynamic search is provided to move from one of the local search results as the initial state to the other local search results. Finally, the availability of the technique is shown by experiments for estimating using functional images and real images.

Citation Download Citation

Shun Ido, Satoshi Arai, Ryo Takamatsu, and Makoto Sato "Dynamic search of Gaussian segmentation", Proc. SPIE 2826, Vision Geometry V, (30 September 1996); https://doi.org/10.1117/12.251806

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