Component-Hypertrees for Image Segmentation
نویسندگان
چکیده
This article introduces the notion of component-hypertree, which models the component-trees of an image at various connectivity levels, and the relations of the nodes/connected components between these levels. This data structure is then used to extend a recently proposed interactive segmentation method based on component-trees. In this multiscale connectivity context, the use of a component-hypertree appears to be less costly than the use of several component-trees. Application examples illustrate the relevance of this approach.
منابع مشابه
A New IRIS Segmentation Method Based on Sparse Representation
Iris recognition is one of the most reliable methods for identification. In general, itconsists of image acquisition, iris segmentation, feature extraction and matching. Among them, iris segmentation has an important role on the performance of any iris recognition system. Eyes nonlinear movement, occlusion, and specular reflection are main challenges for any iris segmentation method. In thi...
متن کاملA New IRIS Segmentation Method Based on Sparse Representation
Iris recognition is one of the most reliable methods for identification. In general, itconsists of image acquisition, iris segmentation, feature extraction and matching. Among them, iris segmentation has an important role on the performance of any iris recognition system. Eyes nonlinear movement, occlusion, and specular reflection are main challenges for any iris segmentation method. In thi...
متن کاملConnected Component Based Word Spotting on Persian Handwritten image documents
Word spotting is to make searchable unindexed image documents by locating word/words in a doc-ument image, given a query word. This problem is challenging, mainly due to the large numberof word classes with very small inter-class and substantial intra-class distances. In this paper, asegmentation-based word spotting method is presented for multi-writer Persian handwritten doc-...
متن کاملUnsupervised Texture Image Segmentation Using MRFEM Framework
Texture image analysis is one of the most important working realms of image processing in medical sciences and industry. Up to present, different approaches have been proposed for segmentation of texture images. In this paper, we offered unsupervised texture image segmentation based on Markov Random Field (MRF) model. First, we used Gabor filter with different parameters’ (frequency, orientatio...
متن کاملQuantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation
Background: Accurate brain tissue segmentation from magnetic resonance (MR) images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM), ...
متن کامل