20.500.12556/RUL-142662 On methods for merging mixture model components suitable for unsupervised image segmentation tasks Unsupervised image segmentation is one of the most important and fundamental tasks in many computer vision systems. Mixture model is a compelling framework for unsupervised image segmentation. A segmented image is obtained by clustering the pixel color values of the image with an estimated mixture model. Problems arise when the selected optimal mixture model contains a large number of mixture components. Then, multiple components of the estimated mixture model are better suited to describe individual segments of the image. We investigate methods for merging the components of the mixture model and their usefulness for unsupervised image segmentation. We define a simple heuristic for optimal segmentation with merging of the components of the mixture model. The experiments were performed with gray-scale and color images. The reported results and the performed comparisons with popular clustering approaches show clear benefits of merging components of the mixture model for unsupervised image segmentation. mixture models parameter estimation clustering unsupervised image segmentation mešani modeli ocena parametrov grozdenje nenadzorovana segmentacija slik true false true Angleški jezik Slovenski jezik Članek v reviji 2022-11-18 09:17:06 2022-11-18 09:17:09 2024-02-15 14:21:58 0000-00-00 00:00:00 2022 0 0 22 str. iss. 22, art. 4301 Vol. 10 Nov. 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 51:004 2227-7390 10.3390/math10224301 129898499 Panic_..._-On_methods_for_merging_mixture_model_components_suitable_for_unsupervised_image_segmentation_tasks.pdf Panic_..._-On_methods_for_merging_mixture_model_components_suitable_for_unsupervised_image_segmentation_tasks.pdf 1 CF0FFB64EA49A1A02F0F0B4D414C6507 b06f75a3d259d81f44c58f5a1cae12078bcf8fb980f7ae333905c75f1accec0f 766949ef-6719-11ed-9c94-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=164114 https://www.mdpi.com/2227-7390/10/22/4301 1 47c5cc97-6719-11ed-9c94-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=164113 Fakulteta za strojništvo 0 0 0