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检索条件"主题词=multi-level image segmentation"
14 条 记 录,以下是11-20 订阅
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A context sensitive Masi entropy for multilevel image segmentation using moth swarm algorithm
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INFRARED PHYSICS & TECHNOLOGY 2019年 第0期98卷 132-154页
作者: Bhandari, Ashish Kumar Rahul, Kusuma Natl Inst Technol Patna Dept Elect & Commun Engn Patna 800005 Bihar India
In this paper, a novel context sensitive energy curve based Masi entropy for image segmentation using moth swarm algorithm (MSA) has been proposed. Although Masi entropy deals with complete probability distribution fo... 详细信息
来源: 评论
A multi-level image thresholding approach using Otsu based on the improved invasive weed optimization algorithm
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SIGNAL image AND VIDEO PROCESSING 2020年 第3期14卷 575-582页
作者: Yue, Xiaofeng Zhang, Hongbo Changchun Univ Technol Sch Mechatron Engn Changchun 130012 Jilin Peoples R China
multi-level thresholding is one of the most popular techniques in image segmentation. However, selecting the optimal thresholds with high accuracy and efficiency is still challenging. In this paper, a novel multi-leve... 详细信息
来源: 评论
A fused contextual color image thresholding using cuttlefish algorithm
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NEURAL COMPUTING & APPLICATIONS 2021年 第1期33卷 271-299页
作者: Bhandari, Ashish Kumar Rahul, Kusuma Shahnawazuddin, Syed Natl Inst Technol Patna Dept Elect & Commun Engn Patna 800005 Bihar India
In this paper, we have proposed a fusion-based context-sensitive Masi energy curve model for multi-level thresholding exploiting cuttlefish algorithm (CFA). The proposed algorithm is simple and very efficient for the ... 详细信息
来源: 评论
A novel local contrast fusion-based fuzzy model for color image multilevel thresholding using grasshopper optimization
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APPLIED SOFT COMPUTING 2019年 81卷 105515-000页
作者: Bhandari, Ashish Kumar Rahul, Kusuma Natl Inst Technol Patna Dept Elect & Commun Engn Patna 800005 Bihar India
The segmentation process is considered the significant step of an image processing system due to its extreme inspiration on the subsequent image analysis. Out of various approaches, thresholding is one of the most pop... 详细信息
来源: 评论