Abstract
Image segmentation is one of the techniques to localize shapes in an image. There are three components of image segmentation which are; image thresholding, edge-based segmentation, and region-based segmentation. In this research, we focused only on one of edge-based segmentation technique which is Hough transform, that can detect circular shapes in an image. However, it was found that there are problems with the existing Hough transform where it is unable to detect a circular shape with unknown radius and it is also unable to detect semicircular shapes. Thus, in this research, Hough transform is enhanced to solve these problems by comparing the pattern of graphs and by looking at the Hough peaks in the Hough transform matrix. In the testing part, results for both semicircle and circle images underwent the process of measuring the quantity of accepted and rejected images using confusion matrix. The results revealed that the accuracy of circle and semicircle detection in modified Hough transform has better performance compared to the existing Hough transform. Thus, this new enhanced technique could be used in the development of a methodology that will be of value in future studies of circle detection in image segmentation; such as in medical area to locate tumors and other pathologies, to locate objects in satellite images, iris recognition, and face recognition.
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Ismail, I., Engkamat, A., Abang Ibrahim, A.F. (2016). Toward Developing an Enhanced Hough Transform Technique for Circle and Semicircle Detection. In: Yacob, N., Mohamed, M., Megat Hanafiah, M. (eds) Regional Conference on Science, Technology and Social Sciences (RCSTSS 2014). Springer, Singapore. https://doi.org/10.1007/978-981-10-0534-3_33
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DOI: https://doi.org/10.1007/978-981-10-0534-3_33
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