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Junction Analysis
CHF 72.70
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32QR3GGKTVQ
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Geliefert zwischen Fr., 13.02.2026 und Mo., 16.02.2026
Details
Gradient-based junctions form key features in such applications as object classification, motion segmentation, and image enhancement. Asymmetric junctions arise from the merging of an odd number of contour end-points such as at a Y-junction. Without an asymmetric representation of such a structure, it will be identified in the same category as X-junctions. This has severe consequences when distinguishing between features in object classification, discerning occlusion from disocclusion in motion segmentation and in properly modeling smoothing boundaries in image enhancement. A novel method is proposed that results in an improved approximation of the underlying contours, through the use of asymmetric junctions. The method combines the ability to represent asymmetric information, as do a number of convolution methods, with the robustness of local support obtained from diffusion schemes. This work investigates several different design paradigms of the asymmetric tensor diffusion algorithm. The proposed approach proved superior to existing techniques by properly accounting for asymmetric junctions over a wide range of scenarios.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783836491013
- Sprache Deutsch
- Größe H8mm x B220mm x T150mm
- Jahr 2013
- EAN 9783836491013
- Format Kartonierter Einband (Kt)
- ISBN 978-3-8364-9101-3
- Titel Junction Analysis
- Autor Shawn Arseneau
- Untertitel Representing Junctions through Asymmetric Tensor Diffusion
- Gewicht 228g
- Herausgeber VDM Verlag Dr. Müller e.K.
- Anzahl Seiten 160
- Genre Mathematik
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