Color image gradients for morphological segmentation: the weighted gradient improved by automatic imposition of weights

“…Let s be the input sequence and s(i) the frame to be segmented. Lotufo, 2004). Anyway, the gradient computation was an intra-frame process, computed by using just the information contained in the frame of interest.…”

Section: Spatio-temporal Gradient Improvementmentioning

confidence: 99%

Watershed From Propagated Markers Improved by the Combination of Spatio-Temporal Gradient and Binding of Markers Heuristics

Flores¹,

Lotufo²

2010

Proceedings of the International Conference on Computer Vision Theory and Applications

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This paper presents the improvement of the watershed from propagated markers, a generic method to interactive segmentation of objects in image sequences, by the inclusion of a temporal gradient to the segmentation framework. Segmentation is done by applying the watershed from markers to a gradient image extracted from the temporal gradient sequence and using markers provided by the binding of markers heuristics. The performance of the improved method is demonstrated by application of a benchmark that supports a quantitative evaluation of assisted segmentation of objects in image sequences. Experimental results provided by the combination of temporal gradient with the binding of markers heuristics show that the proposed improvement can decrease the number of human interferences and the time required to process the sequences.

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“…• support for segmentation of color images using the weighted gradient, as described in (Flores et al, 2004). The user can use either the automatically computed weights or arbitrary weights for each gradient considered (the weighted gradient consists in a weighted sum of gradients defined on each band of the image: hue, saturation and brightness).…”

Section: Additional Featuresmentioning

confidence: 99%

Interactive Image Segmentation With Integrated Use of the Markers and the Hierarchical Watershed Approaches

Klava

Hirata

2009

Proceedings of the Fourth International Conference on Computer Vision Theory and Applications

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The watershed transform is a well-known approach for image segmentation. Watershed from markers and hierarchical watershed are derived from the watershed transform and are suitable for interactive image segmentation: in the former, the user can edit markers and control the segmentation result; in the latter, the user can select an image partition from a nested set of partitions. We investigate and propose ways to transition from one approach to other. Such transitions can be used to integrate both approaches in such a way that allow us to make full use of the strengths of both. We present examples that illustrate the use of the proposed transitions in conjunction with several interaction possibilities from both approaches.

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Color image gradients for morphological segmentation: the weighted gradient improved by automatic imposition of weights

Cited by 7 publications

References 12 publications

Watershed from propagated markers: An interactive method to morphological object segmentation in image sequences

Watershed from propagated markers: An interactive method to morphological object segmentation in image sequences

Watershed From Propagated Markers Improved by the Combination of Spatio-Temporal Gradient and Binding of Markers Heuristics

Interactive Image Segmentation With Integrated Use of the Markers and the Hierarchical Watershed Approaches

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