Alazab, MamounIslam, MofakharulVenkatraman, Sitalakshmi2015-12-13December 19783642104381http://hdl.handle.net/1885/72770Image 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.Keywords: Automated segmentation; Automatic diagnosis; Automatic image segmentation; Dental diagnosis; Digital forensic; Digital image; False boundary; Human errors; Industrial inspections; Labour-intensive; Manual segmentation; Medical treatment; Real-time techniq Automatic diagnosis; Digital forensic; False boundary; Image segmentation; Region growing200910.1007/978-3-642-10439-8_142016-02-24