Abstract
For the model of active contours with group similarity (ACGS), a rank constraint for a group of evolving contours is defined to keep the shape similarity. ACGS obtains robust results in extracting a single object with missing or misleading features. However, with one initial contour, it could not extent to multiple objects segmentation because low‐rank property will not hold in some image sequences. Besides, ACGS is affected by nontarget objects. In this paper, an active contour model based on block similarity of shapes is proposed to extend the ACGS model to realize multiple objects extraction. For a sequence of image with multiple objects, a model for multiple objects extraction is constructed by combining sparse decomposition and ACGS; second, a block low‐rank constraint is proposed to constrain the similarity of these evolving contours in every block; finally, segmentation results are obtained through iterative evolutions. Experimental results show the proposed method could segment images with multiple targets, and it improves the robust segmentation performance of sequence of image when the features of multiobjects are missing or misleading.
Highlights
Ere are broadly two types of active contour models (ACMs) according to the representation of contour, i.e., parametric active contour model [4, 7] and geometric active contour model [8,9,10,11,12]
Geometric active contour model, which is known as implicit active contour model, has been presented [8] based on level set method (LSM) [8, 10]
LSM o ers great exibility for curve topology. erefore, topological exibility is a major advantage of geometric active contour model, which is desirable in detecting multiple objects [11]
Summary
Object segmentation is an important research topic in many elds, such as computer vision and image recognition [1]. In order to avoid training of massive data and effectively deal with the affection caused by the interference information, an active contour with group similarity (ACGS) is proposed for single target extraction in a sequence of image [15]. It can be regarded as an unsupervised prior shape model. In this paper, based on ACGS [15] and sparse decomposition method [30, 31], ACGS is extended to realize multiple objects segmentation of image sequence with parametric active contour model.
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