Generalized flooding and multicue PDE-based image segmentation

Sofou, A; Maragos, P

dc.contributor.author	Sofou, A	en
dc.contributor.author	Maragos, P	en
dc.date.accessioned	2014-03-01T01:28:30Z
dc.date.available	2014-03-01T01:28:30Z
dc.date.issued	2008	en
dc.identifier.issn	1057-7149	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18858
dc.subject	Feature extraction	en
dc.subject	Morphological filtering	en
dc.subject	Partial differential equation (PDE)	en
dc.subject	Segmentation	en
dc.subject	Topographic flooding	en
dc.subject	U + V image decomposition	en
dc.subject	Watershed	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Feature extraction	en
dc.subject.other	Image analysis	en
dc.subject.other	Image quality	en
dc.subject.other	Mathematical morphology	en
dc.subject.other	Partial differential equations	en
dc.subject.other	Image decomposition	en
dc.subject.other	Morphological filtering	en
dc.subject.other	Topographic flooding	en
dc.subject.other	Image segmentation	en
dc.subject.other	algorithm	en
dc.subject.other	article	en
dc.subject.other	artificial intelligence	en
dc.subject.other	automated pattern recognition	en
dc.subject.other	computer assisted diagnosis	en
dc.subject.other	image enhancement	en
dc.subject.other	methodology	en
dc.subject.other	reproducibility	en
dc.subject.other	sensitivity and specificity	en
dc.subject.other	three dimensional imaging	en
dc.subject.other	Algorithms	en
dc.subject.other	Artificial Intelligence	en
dc.subject.other	Image Enhancement	en
dc.subject.other	Image Interpretation, Computer-Assisted	en
dc.subject.other	Imaging, Three-Dimensional	en
dc.subject.other	Pattern Recognition, Automated	en
dc.subject.other	Reproducibility of Results	en
dc.subject.other	Sensitivity and Specificity	en
dc.title	Generalized flooding and multicue PDE-based image segmentation	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TIP.2007.916156	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TIP.2007.916156	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	Image segmentation remains an important, but hard-to-solve, problem since it appears to be application dependent with usually no a priori information available regarding the image structure. Moreover, the increasing demands of image analysis tasks in terms of segmentation results' quality introduce the necessity of employing multiple cues for improving image segmentation results. In this paper, we attempt to incorporate cues such as intensity contrast, region size, and texture in the segmentation procedure and derive improved results compared to using individual cues separately. We emphasize on the overall segmentation procedure, and we propose efficient simplification operators and feature extraction schemes, capable of quantifying important characteristics, like geometrical complexity, rate of change in local contrast variations, and orientation, that eventually favor the final segmentation result. Based on the well-known morphological paradigm of watershed transform segmentation, which exploits intensity contrast and region size criteria, we investigate its partial differential equation (PDE) formulation, and we extend it in order to satisfy various flooding criteria, thus making it applicable to a wider range of images. Going a step further, we introduce a segmentation scheme that couples contrast criteria in flooding with texture information. The modeling of the proposed scheme is done via PDEs and the efficient incorporation of the available contrast and texture information, is done by selecting an appropriate cartoon-texture image decomposition scheme. The proposed coupled segmentation scheme is driven by two separate image components: artoon U (for contrast information) and texture component V. The performance of the proposed segmentation scheme is demonstrated through a complete set of experimental results and substantiated using quantitative and qualitative criteria. © 2008 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Image Processing	en
dc.identifier.doi	10.1109/TIP.2007.916156	en
dc.identifier.isi	ISI:000253272300010	en
dc.identifier.volume	17	en
dc.identifier.issue	3	en
dc.identifier.spage	364	en
dc.identifier.epage	376	en