Fast segmentation based on a hybrid of clustering and morphological approaches
Fac. of Electron. & Telecommun., Hanoi Univ. of Technol., HanoiDOI: 10.1109/CCE.2008.4578952 Conference: Communications and Electronics, 2008. ICCE 2008. Second International Conference on
Source: IEEE Xplore
This paper proposes a fast segmentation method for still image based on a hybrid of clustering and morphological segmentation approach. The objective of the clustering is to partition an input image into a number of clusters such that the gray levels within each cluster are similar. The clustered image is further processed by using morphological segmentation approach, in which a seeded region growing however plays a role of the decision tool instead of a watershed algorithm for a remarkable improvement of processing time. The performance of the proposed method is evaluated by comparing its region-based coding results with those of the morphological watershed-based segmentation method and the split-and-merge algorithm. The experiments results showed that region-based coding using the proposed algorithm yields PSNR improvement of about 1.5 dB over the morphological watershed-based method. Especially, the total time elapsed to segment an image using the proposed method is reduced about 1/6 and 1/3 compared with those of the watershed-based segmentation and the split-and-merge methods, respectively.
Full-text previewDOI: · Available from: tainguyenso.vnu.edu.vn
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.