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Region-based segmentation of images using syntactic visual features

Adamek, Tomasz and O'Connor, Noel E. and Murphy, Noel (2005) Region-based segmentation of images using syntactic visual features. In: WIAMIS 2005 - 6th International Workshop on Image Analysis for Multimedia Interactive Services, 13-15 April 2005, Montreux, Switzerland.

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This paper presents a robust and efficient method for segmentation of images into large regions that reflect the real world objects present in the scene. We propose an extension to the well known Recursive Shortest Spanning Tree (RSST) algorithm based on a new color model and so-called syntactic features [1]. We introduce practical solutions, integrated within the RSST framework, to structure analysis based on the shape and spatial configuration of image regions. We demonstrate that syntactic features provide a reliable basis for region merging criteria which prevent formation of regions spanning more than one semantic object, thereby significantly improving the perceptual quality of the output segmentation. Experiments indicate that the proposed features are generic in nature and allow satisfactory segmentation of real world images from various sources without adjustment to algorithm parameters.

Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Subjects:Computer Science > Digital video
Computer Science > Information retrieval
Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:453
Deposited On:21 May 2008 by DORAS Administrator. Last Modified 16 Feb 2009 13:52

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