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

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)

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- 被引次数: 0
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

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

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。
- 模糊红外图像 /
- 模板特征 /
- 免疫网络 /
- 靶向免疫疗法
Abstract: Hand infrared trace images can not clearly reflect the original contact contour of hand, which belong to a special kind of infrared blurred images. Inspired by biological immune, an artificial targeting immunotherapy is proposed to extract the hand target. Firstly, according to the feature of temporal correlation, the innate immune recognition is designed to preliminary segmentation. Secondly, according to the immune presentation, a concentric circles template based on thermal diffusion is defined to extract features. Then adaptive immune recognition is applied to the fuzzy pixels set based on the obtained template features. Finally, for the detected finger valley and fingertips lesions, targeted therapy is implemented to keep the shape of the hand. The proposed algorithm is compared with watershed method, SOM network and recent research achievements. Experimental results show that the proposed algorithm exhibits better extraction performance, meanwhile the application time of thermal trace images is extended.
- Blurred infrared images /
- Template features /
- Immune network /
- Targeted immunotherapy

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参考文献(27)

XIONG Zonglong, YANG Kuntao, DING Wenxiu, et al. Computational and experimental research on infrared trace by human being contact[J]. Applied Optics, 2010, 49(18): 3587-3595. doi: 10.1364/AO.49.003587.

韩玉阁, 成志铎, 任登凤, 等. 装甲车辆与地面背景的热交互作用及红外仿真[J]. 红外与激光工程, 2013, 42(1): 20-25.

HAN Yuge, CHENG Zhiduo, REN Dengfeng, et al. Thermal interactions and infrared simulation of armored vehicles and ground background[J]. Infrared and Laser Engineering, 2013, 42(1): 20-25.

FU Dongmei, YU Xiao, and TONG Hejun. Target extraction of blurred infrared image with an immune network template algorithm[J]. Optics Laser Technology, 2014, 56(1): 102-106. doi: 10.1016/j.optlastec.2013.07.019.

付冬梅, 于晓, 童何俊. 基于免疫模板聚类的模糊中波红外图像目标提取[J]. 光谱学与光谱分析, 2014, 34(3): 673-676. doi: 10.3964/j.issn.1000-0593(2014)03-0673-04.

FU Dongmei, YU Xiao, and TONG Hejun. Extracting target blurred midwave infrared image based on immune template clustering[J]. Spectroscopy and Spectral Analysis, 2014, 34(3): 673-676. doi: 10.3964/j.issn.1000-0593(2014)03-0673-04.

李辉. 红外序列图像中手部痕迹目标提取的立体化模板研究[D]. [硕士论文], 北京科技大学, 2015.

LI Hui. Research on hand trace target extraction using 3D template from sequence infrared images[D]. [Master dissertation], University of Science and Technology Beijing, 2015.

LI Hui, FU Dongmei, and YANG Tao. Hand target extraction from infrared images with descriptor based on pixel temporal characteristics[C]. 2015 8th International Congress on Image Signal Processing(CISP), Changchun, China, 2015: 458-463.

FAWAZ A A and ALLAHVERDI A. An artificial immune system heuristic for two-stage multi-machine assembly scheduling problem to minimize total completion time[J]. Journal of Manufacturing Systems, 2013, 32(4): 825-830. doi: 10.1016/j.jmsy.2013.06.001.

CHARLES A J, PAUL T, MARK W, et al. Janeway,s Immunobiology[M]. 5th Version, Beijing China: Science Press, 2007: 107-140.

SHARMA P, ALLISON J P, et al. Immune checkpoint targeting in cancer therapy: Toward combination strategies with curative potential[J]. Cell, 2015, 161(2): 205-214. doi: 10.1016/j.cell.2015.03.030.

MEHRAD E and KARIM F. Automatic traffic monitoring from satellite images using artificial immune system[J]. Lecture Notes in Computer Science, 2010: 170-179. doi: 10.1007/978-3-642-14980-1_16.

AL-SHESHTAWI K A, ABDUL-KADER H M, and ISMAIL N A. Artificial immune clonal selection classification algorithms for classifying malware and benign processes using API call sequences[J]. International Journal of Computer Science and Network Security, 2010, 10(4): 31-39.

KARAKOSE M. Reinforcement learning based artificial immune classifier[J]. Scientific World Journal, 2013, 2013: 581846. doi: 10.1155/2013/581846.

ZHAO Mengling and LIU Hongwei. An associate rules mining algorithm based on artificial immune network for SAR image segmentation[J]. Mathematical Problems in Engineering, 2015: 1-14. doi: 10.1155/2015/839081.

AHMADI S D and SAJEDI H. Image steganography with Artificial Immune System[C]. IEEE Artificial Intelligence and Robotics, Qazvin, Iran, 2017: 45-50. doi: 10.1109/RIOS.2017. 7956442.

于晓. 红外图像中手部痕迹目标的提取研究[D]. [博士论文], 北京科技大学, 2014.

YU Xiao. Research on hand trace target extraction from infrared image [D]. [Ph.D. dissertation], Beijing: University of Science and Technology Beijing, 2014.

尚振宏, 刘明业. 基于欧氏距离的拐点检测算法[J]. 计算机应用, 2004, 24(10): 88-91.

SHANG Zhenhong and LIU Mingye. Corner detection algorithm based on Euclidean distance[J]. Computer Applications, 2004, 24(10): 88-91.

刘淑萍, 刘羽, 於俊, 等. 结合手指检测和HOG特征的分层静态手势识别[J]. 中国图象图形学报, 2015, 20(6): 781-788. doi: 10.11834/jig.20150607.

LIU Shuping, LIU Yu , YU Jun, et al. Hierarchical static hand gesture recognition by combining finger detection and HOG features[J]. Journal of Image and Graphics, 2015, 20(6): 781-788. doi: 10.11834/jig.20150607.

杨焘, 付冬梅. 流形正则化多核模型的模糊红外目标提取[J]. 工程科学学报, 2016, 38(6): 876-885. doi: 10.13374/j.issn 2095-9389.2016.06.019.

YANG Tao and FU Dongmei. Extraction of blurred infrared targets based on a manifold regularized multiple-kernel model[J]. Chinese Journal of Engineering, 2016, 38(6): 876-885. doi: 10.13374/j.issn2095-9389.2016.06.019.

CRDENES R, BACH M, CHI Y, et al. Multimodal evaluation for medical image segmentation[C]. International Conference on Computer Analysis of Images and Patterns, Vienna, Austria, 2007: 229-236. doi: 10.1007/978-3-540- 74272-2_29.

BABALOLA K O, PATENAUDE B, and ALJABAR P. An evaluation of four automatic methods of segmenting the subcortical structures in the brain[J]. Neuroimage, 2009, 47(4): 1435-1447. doi: 10.1016/j.neuroimage.2009.05.029.

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