Video region segmentation by spatio-temporal watersheds (original) (raw)

An accurate semi-automatic segmentation scheme based on watershed and change detection mask

2005

abstract This paper presents a region-based segmentation method extracting automatically moving objects from video sequences. Non-moving objects can also be segmented by using a graphical user interface. The segmentation scheme is inspired from existing methods based on the watershed algorithm. The over-segmented regions resulting from the watershed are first organized in a binary partition tree according to a similarity criterion. This tree aims to determine the fusion order.

Watershed data aggregation for mean-shift video segmentation

2007

abstract Object segmentation is considered as an important step in video analysis and has a wide range of practical applications. In this paper we propose a novel video segmentation method, based on a combination of watershed segmentation and mean-shift clustering. The proposed method segments video by clustering spatio-temporal data in a six-dimensional feature space, where the features are spatio-temporal coordinates and spectral attributes.

Watershed approaches for color image segmentation

This paper presents and discusses different approaches to extend the watershed transform, which is the classical segmentation tool in gray-scale mathematical morphology, to the case of color or, more generally speaking, multi- component images. Different strategies are presented and a special attention is paid to the "bit mixing approach". This method bijectively mapps multi-dimensional data into a mono-dimensional space. It thus allows to use directly the usual scalar watershed algorithm on the encoded data, nevertheless taking explicitely into account their vectorial structure.

Hybrid image segmentation using watersheds and fast region merging

1998

Abstract A hybrid multidimensional image segmentation algorithm is proposed, which combines edge and region-based techniques through the morphological algorithm of watersheds. An edge-preserving statistical noise reduction approach is used as a preprocessing stage in order to compute an accurate estimate of the image gradient. Then, an initial partitioning of the image into primitive regions is produced by applying the watershed transform on the image gradient magnitude.

Modified Watershed Algorithm for Segmentation of 2D Images

2000

With the repaid advancement of computer technology, the use of computer-based technologies is increasing in different fields of life. Image segme ntation is an important problem in different fields of image processing and computer vision. Ima ge segmentation is the process of dividing images according to its characteristic e.g., color and objects present in the images. Different methods are presented