A new method for automatic salient object segmentation is presented.Salient object segmentation is an important research area in the field of object recognition,image retrieval,image editing,scene reconstruction,and 2...A new method for automatic salient object segmentation is presented.Salient object segmentation is an important research area in the field of object recognition,image retrieval,image editing,scene reconstruction,and 2D/3D conversion.In this work,salient object segmentation is performed using saliency map and color segmentation.Edge,color and intensity feature are extracted from mean shift segmentation(MSS)image,and saliency map is created using these features.First average saliency per segment image is calculated using the color information from MSS image and generated saliency map.Then,second average saliency per segment image is calculated by applying same procedure for the first image to the thresholding,labeling,and hole-filling applied image.Thresholding,labeling and hole-filling are applied to the mean image of the generated two images to get the final salient object segmentation.The effectiveness of proposed method is proved by showing 80%,89%and 80%of precision,recall and F-measure values from the generated salient object segmentation image and ground truth image.展开更多
We report an NMR experimental realization of a rapid quantum deletion algorithm that deletes marked states in an unsorted database.Unlike classical deletion,where search and deletion are equivalent,quantum deletion ca...We report an NMR experimental realization of a rapid quantum deletion algorithm that deletes marked states in an unsorted database.Unlike classical deletion,where search and deletion are equivalent,quantum deletion can be implemented with only a single query,which achieves exponential speed-up compared to the optimal classical analog.In the experimental realization,the GRAPE algorithm was used to obtain an optimized NMR pulse sequence,and the efficient method of maximum-likelihood has been used to reconstruct the experimental output state.展开更多
文摘A new method for automatic salient object segmentation is presented.Salient object segmentation is an important research area in the field of object recognition,image retrieval,image editing,scene reconstruction,and 2D/3D conversion.In this work,salient object segmentation is performed using saliency map and color segmentation.Edge,color and intensity feature are extracted from mean shift segmentation(MSS)image,and saliency map is created using these features.First average saliency per segment image is calculated using the color information from MSS image and generated saliency map.Then,second average saliency per segment image is calculated by applying same procedure for the first image to the thresholding,labeling,and hole-filling applied image.Thresholding,labeling and hole-filling are applied to the mean image of the generated two images to get the final salient object segmentation.The effectiveness of proposed method is proved by showing 80%,89%and 80%of precision,recall and F-measure values from the generated salient object segmentation image and ground truth image.
基金supported by the National Natural Science Foundation of China(Grant Nos.11175094 and 91221205)the National Basic Research Program of China(Grant No.2011CB9216002)
文摘We report an NMR experimental realization of a rapid quantum deletion algorithm that deletes marked states in an unsorted database.Unlike classical deletion,where search and deletion are equivalent,quantum deletion can be implemented with only a single query,which achieves exponential speed-up compared to the optimal classical analog.In the experimental realization,the GRAPE algorithm was used to obtain an optimized NMR pulse sequence,and the efficient method of maximum-likelihood has been used to reconstruct the experimental output state.
