6533b7dcfe1ef96bd1273511

RESEARCH PRODUCT

A segmentation algorithm for noisy images

Serge MiguetHocine CherifiSoufiane Rital

subject

020203 distributed computingHypergraphMathematics::Combinatorics[ INFO ] Computer Science [cs]Computer sciencebusiness.industrySegmentation-based object categorizationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationImage processing02 engineering and technologyImage segmentation[INFO] Computer Science [cs]020202 computer hardware & architectureComputer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)SegmentationComputer vision[INFO]Computer Science [cs]Artificial intelligencebusinessAlgorithmMathematicsofComputing_DISCRETEMATHEMATICS

description

International audience; This paper presents a segmentation algorithm for gray-level images and addresses issues related to its performance on noisy images. It formulates an image segmentation problem as a partition of a weighted image neighborhood hypergraph. To overcome the computational difficulty of directly solving this problem, a multilevel hypergraph partitioning has been used. To evaluate the algorithm, we have studied how noise affects the performance of the algorithm. The alpha-stable noise is considered and its effects on the algorithm are studied. Key words : graph, hypergraph, neighborhood hypergraph, multilevel hypergraph partitioning, image segmentation and noise removal.

yearjournalcountryeditionlanguage
2005-09-05
https://hal.archives-ouvertes.fr/hal-01589733