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A new data structure for the implementation of unsupervised texture segmentation

Padmapriya, N., Pradeep, P.P. and Whelan, Paul F. ORCID: 0000-0001-9230-7656 (2002) A new data structure for the implementation of unsupervised texture segmentation. In: ISSC 2002 - Irish Signals and Systems Conference 2002, 25-26 Jun 2002, ISSC 2002 - Irish Signals and Systems Conference 2002.

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Abstract

In this paper, we propose a novel technique to implement an algorithm for unsupervised texture segmentation. Local Binary Patterns (LBP) have been demonstrated to provide a robust and efficient framework for texture segmentation. The distribution of local binary pattern and the contrast measure is used to evaluate the similarity between the adjacent image regions during the segmentation operation. The algorithm uses a new data structure. The existing data structures such as trees and graphs are modified to construct a quadtree and mergegraph. Quadtree is used for splitting the image into blocks of roughly uniform textures and mergegraph is used for merging similar adjacent regions. The algorithm has been tested using mosaic images consisting of various textures, in addition to natural scenes. This approach proved to yield computationally effcient segmentation of images.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:computer vision; image analysis; Local Binary Pattern; Quadtree; Splittree; Mergegraph; Segmentation algorithm
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:18813
Deposited On:15 Aug 2013 13:08 by Mark Sweeney . Last Modified 03 Sep 2020 10:47

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