Learning tool of image segmentation techniques for new learners

• Main Author: Gan, Song Chiew
• Format: Thesis
• Language: English
• Published: 2013
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/34638/5/GanSongChiewMFKE2013.pdf; http://eprints.utm.my/id/eprint/34638/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:67954?site_name=Restricted Repository

Image segmentation is an essential step for other image processing steps. There are plenty of image processing tools in the market but most of them are not research and education based. There are only few from the remaining ones which are suitable and widely being used by new leaner and MATLAB is one of them. Although MATLAB is open source and well established but limited interactive applications focusing on image segmentation targeting for new learners. Discussion and open forum are mostly reviewing advance image processing techniques. However, the fundamental of image segmentation cannot be neglected as it affects all other image processing applications later. Most of the time, new learner spent longer time understanding the tool instead of familiarize with the algorithm and theory behind the image segmentation. The purpose of the project is to develop an interactive learning tool for image segmentation targeting for new learners. In this project, an interactive Graphical User Interface, GUI which is based on MATLAB is being introduced as survey shows that undergraduates from Universiti Teknologi Malaysia, UTM prefer and more frequent to use MATLAB solving image processing related issues. The Learning Tool of Image Segmentation covering most of the fundamental images segmentation techniques; such as point detection, line detection, edge detection, thresholding, region growing, Watershedding and K-Mean clustering. Information displayed on each and every step helps users to understand better the algorithm, theory and Application Programming Interface, API for the method. Guidance and questions at Message Window increase the curiosity of image segmentation and custom segmentation options motivates new learners for trial and error.