Hypothesis-based image segmentation

A Machine Learning Approach

von Alexander Denecke

164 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

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.

• Themen: Informatik und Informationstechnologie Informatik
• ISBN: 9783838133713
• Sprache: Englisch
• Erscheinungsdatum: 09.07.2015
• Größe: 220 x 150 mm
• Verlag: Südwestdeutscher Verlag für Hochschulschriften AG Co. KG