Towards automatic image segmentation using optimised region growing technique

Mamoun Alazab*, Mofakharul Islam, Sitalakshmi Venkatraman

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

10 Citations (Scopus)


Image analysis is being adopted extensively in many applications such as digital forensics, medical treatment, industrial inspection, etc. primarily for diagnostic purposes. Hence, there is a growing interest among researches in developing new segmentation techniques to aid the diagnosis process. Manual segmentation of images is labour intensive, extremely time consuming and prone to human errors and hence an automated real-time technique is warranted in such applications. There is no universally applicable automated segmentation technique that will work for all images as the image segmentation is quite complex and unique depending upon the domain application. Hence, to fill the gap, this paper presents an efficient segmentation algorithm that can segment a digital image of interest into a more meaningful arrangement of regions and objects. Our algorithm combines region growing approach with optimised elimination of false boundaries to arrive at more meaningful segments automatically. We demonstrate this using X-ray teeth images that were taken for real-life dental diagnosis.

Original languageEnglish
Title of host publicationAI 2009: Advances in artificial intelligence
Subtitle of host publication22nd Australasian Joint Conference, Melbourne, Australia, December 2009, Proceedings
EditorsAnn Nicholson, Xiaodong Li
Place of PublicationBerlin; Heidelberg
PublisherSpringer, Springer Nature
Number of pages9
ISBN (Print)364210438X, 9783642104381
Publication statusPublished - 2009
Event22nd Australasian Joint Conference on Artificial Intelligence, AI 2009 - Melbourne, VIC, Australia
Duration: 1 Dec 20094 Dec 2009

Publication series

NameLecture Notes in Artificial Intelligence
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other22nd Australasian Joint Conference on Artificial Intelligence, AI 2009
CityMelbourne, VIC


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