You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
1 November 1989Principles and Applications of a New Cooperative Segmentation Methodology
This paper illustrates three principles of a generic segmentation method, and their application to two particular cases of scene analysis. These cases refer to different applications, as the target tracking from infrared imagery described in [BPZ89], or the 3D reconstruction of indoor / outdoor scene, in man-made environments, from visible imagery described in [BBHZ89]. The first principle of the proposed segmentation methodology is in considering future implementation on parallel computers either of the MIMD (Multiple Instructions Multiple Data) or SIMD type (Single Instruction Multiple Data). The developped algorithms must exploit the possibilities of these computers. The second principle is the early introduction of an a priori knowledge. So the segmentation method is specific to a particular case of scene analysis. It relies on both a physical model related to the image formation (depending totally on the spectral domain, here IR or visible) , and a conceptual model related to the application, here tracking or 3D reconstruction. This introduction of knowledge allows the system to segment "finely" only certain interesting parts of the image. The third principle is in forcing cooperative or guided segmentation. For instance, robust segmentation algorithms often require simultaneous information about homogeneity and disparity properties of the image. The proposed method, which implies a great cooperation between edge and region detectors, enhancing these previous properties, satisfies this requirement.
The alert did not successfully save. Please try again later.
P. Bonnin, B. Zavidovique, "Principles and Applications of a New Cooperative Segmentation Methodology," Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); https://doi.org/10.1117/12.970078