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Anglický jazyk
Hypothesis-based image segmentation
Autor: Alexander Denecke
This thesis addresses the ¿gure-ground segmentation problem in the context of complex systems for automatic object recognition. Firstly the problem of image segmentation in general terms is introduced, followed by a discussion about its importance for online... Viac o knihe
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O knihe
This thesis addresses the ¿gure-ground segmentation problem in the context of complex systems for automatic object recognition. Firstly the problem of image segmentation in general terms is introduced, followed by a discussion about its importance for online and interactive acquisition of visual representations. Secondly a machine learning approach using arti¿cial neural networks is presented. This approach on the basis of Generalized Learning Vector Quantization is investigated in challenging scenarios such as the real-time ¿gure-ground segmentation of complex shaped objects under continuously changing environment conditions. The ability to ful¿ll these requirements characterize the novelty of the approach compared to state-of-the-art methods. Finally the proposed technique is extended in several aspects, which yields a framework for object segmentation that is applicable to improve current systems for visual object learning and recognition.
- Vydavateľstvo: Südwestdeutscher Verlag für Hochschulschriften AG Co. KG
- Rok vydania: 2015
- Formát: Paperback
- Rozmer: 220 x 150 mm
- Jazyk: Anglický jazyk
- ISBN: 9783838133713
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