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基于人工靶向免疫疗法的红外手部痕迹目标提取

付冬梅 孙静 杨焘

付冬梅, 孙静, 杨焘. 基于人工靶向免疫疗法的红外手部痕迹目标提取[J]. 电子与信息学报, 2018, 40(2): 346-352. doi: 10.11999/JEIT170282
引用本文: 付冬梅, 孙静, 杨焘. 基于人工靶向免疫疗法的红外手部痕迹目标提取[J]. 电子与信息学报, 2018, 40(2): 346-352. doi: 10.11999/JEIT170282
FU Dongmei, SUN Jing, YANG Tao. Target Extraction of Hand Infrared Trace Images Based on Artificial Targeting Immunotherapy[J]. Journal of Electronics & Information Technology, 2018, 40(2): 346-352. doi: 10.11999/JEIT170282
Citation: FU Dongmei, SUN Jing, YANG Tao. Target Extraction of Hand Infrared Trace Images Based on Artificial Targeting Immunotherapy[J]. Journal of Electronics & Information Technology, 2018, 40(2): 346-352. doi: 10.11999/JEIT170282

基于人工靶向免疫疗法的红外手部痕迹目标提取

doi: 10.11999/JEIT170282
基金项目: 

国家自然科学基金(61272358),北京市重点学科共建项目(XK100080537)

Target Extraction of Hand Infrared Trace Images Based on Artificial Targeting Immunotherapy

Funds: 

The National Natural Science Foundation of China (61272358), Beijing Key Discipline Development Program (XK100080537)

  • 摘要: 红外手部热痕迹图像是特殊的模糊图像,该文提出一种人工靶向免疫疗法对其进行手部目标提取。首先依据序列图像中像素灰度的变化趋势设计了先天性免疫识别进行初分割;然后借鉴免疫的提呈机制,根据热扩散特性定义同心圆模板提取特征;基于模板特征对模糊像素集适应性免疫识别;最后,指尖指谷病变检测分析,实施靶向治疗,保证了手的形态特征。与分水岭、SOM网络以及近几年研究成果进行了比较,表明提出的算法在目标提取率、绝对误差率均优于现有算法,提取结果更符合手的形态,同时扩展了应用热痕迹信息的时间跨度。
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出版历程
  • 收稿日期:  2017-04-01
  • 修回日期:  2017-09-18
  • 刊出日期:  2018-02-19

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