综述

指纹皱纹研究的现状及展望

  • 曾浩然 ,
  • 刘康康 ,
  • 罗亚平
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  • 1.中国人民公安大学,北京 100038
    2.安徽省公安教育研究院,合肥 230031
曾浩然,硕士研究生,主要研究方向为痕迹检验技术。E-mail: z875783473@163.com
罗亚平,主要研究方向为痕迹检验技术。E-mail: luoyaping@ppsuc.edu.cn

收稿日期: 2023-05-15

  修回日期: 2023-09-12

  网络出版日期: 2024-06-04

基金资助

国家社科基金重大项目(20&ZD257)

Current status and prospects of the research on finger crease features

  • ZENG Haoran ,
  • LIU Kangkang ,
  • LUO Yaping
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  • 1. People’s Public Security University of China, Beijing 100038
    2. Anhui Public Security Education Research Institute, Hefei 230031

Received date: 2023-05-15

  Revised date: 2023-09-12

  Online published: 2024-06-04

摘要

指纹是手指指腹上由乳突纹线构成的花纹结构,在日常生活中扮演着重要角色。指纹皱纹是皮纹学中非皮嵴纹构型和屈肌褶纹的一个显著特征,因其在捺印指印时表现为正常乳突纹线在不同方向上中断,从而形成白色条纹,因此又称为指纹白线。指纹皱纹的形成和表现与皮肤疾病、民族种群和个体差异等因素相关联,故该特征在皮纹学、医学、法庭科学和计算机识别等领域具有重要的应用价值。本文对指纹皱纹的基本属性进行了整理,重点介绍了其研究进展,并初步展望了未来的研究方向,希望为其科学研究提供有益的参考。

本文引用格式

曾浩然 , 刘康康 , 罗亚平 . 指纹皱纹研究的现状及展望[J]. 人类学学报, 2024 , 43(03) : 518 -528 . DOI: 10.16359/j.1000-3193/AAS.2024.0010

Abstract

The fingerprint is the main morphological area on the finger, which plays an important role in daily life. The fingerprint crease is an obvious feature of non-cutaneous ridge configuration and flexor fold in dermatology. It’s also called fingerprint white lines by many scholars because of the white stripes that can interrupt the normal friction ridge in different directions in the fingerprinting. Due to the obvious morphological and structural characteristics of finger crease features, which are common in modern people, and their formation and performance are related to skin diseases, ethnic populations, individual differences and other factors, finger crease features have gradually entered the field of vision of researchers at home and abroad in the field of anthropology, medicine, forensic science and computer image recognition. Current research on finger crease features includes the following aspects:1) to explore the influencing factors of finger crease features, such as pressure, age, season, ethnicity, etc; 2) to explore the correlation between finger crease features and skin diseases and mental diseases; 3) to explore the identification value of finger crease features in the field of forensic science and to dig the personal information carried by them; 4) Explore the algorithm for automatic recognition and extraction of finger crease features. At the same time, the following prospects are put forward for the study of finger crease features: 1) Develop the standardized measurement methods and evaluation criteria for finger crease features, explore the identification value of finger crease features by using the likelihood ratio theory, and discuss which fingerprint characteristic level finger crease features should belong to; 2) OCT technology was used to explore the expression of finger crease features in the dermis and epidermis, and to explore the formation mechanism of finger crease features; 3) Yolov5 target recognition technology was used to realize automatic recognition and extraction of finger crease features. As a result, a comprehensive and in-depth analysis and introduction were conducted to sort out the primary attributes and the current status of finger crease features’ research home and abroad. In the end, we also give a personal perspective on the future direction and the remaining challenges in the finger crease features related field. New exciting progress is expected in the development of related field with continued interest and attention to the finger crease features.

参考文献

[1] 姚中港. 指纹细点线的形态变化及识别方法研究[D]. 北京: 中国人民公安大学, 2014, 4-5
[2] 钟新文, 张忠良. 手印学[M]. 北京: 中国人民公安大学出版社, 2014, 223-225
[3] B·肖曼, M·阿尔特, 姚荷生. 皮肤纹理学与疾病[M]. 江苏: 江苏科学技术出版社, 1984, 122-123
[4] 郭少波, 王芫, 王炎, 等. 探析高分辨率指纹特定条件下三级特征的稳定性[J]. 中国司法鉴定, 2013, 1:56-61
[5] 张瑾, 刘晓明. 运用指印特征提升疑难指印鉴定率[J]. 中国人民公安大学学报(自然科学版), 2016, 22(1):4-10
[6] 罗亚平, 郭威. 指纹学教程[M]. 北京: 中国人民公安大学出版社, 2010, 85-86
[7] Vernon DSG. Automatic detection of secondary creases in fingerprints[J]. Optical Engineering, 1993, 32(10): 2616-2623
[8] Cummins H, Midlo C. Finger prints, palms and soles: an introduction to dermatoglyphics[M]. New York: Dover Publications, 1961, 41-42
[9] 韦向东. 利用指纹伤疤印痕确定犯罪嫌疑人1例[J]. 刑事技术, 2014, 5: 21
[10] Richmond S. Do fingerprint ridges and characteristics within ridges change with pressure?[J]. Australian Federal Police, Forensic Services, 2004, 5: 46-47
[11] Silva LRV, Mizokami L, Vieira PR, et al. Longitudinal and retrospective study has demonstrated morphometric variations in the fingerprints of elderly individuals[J]. Forensic science international, 2016, 259: 41-46
[12] Monson KL, Roberts MA, Knorr KB, et al. The permanence of friction ridge skin and persistence of friction ridge skin and impressions: a comprehensive review and new results[J]. Forensic science international, 2019, 297: 111-131
[13] 宋焕庭, 唐玮, 张丽梅, 等. 指纹与年龄相关性的量化分析[J]. 人类学学报, 2022, 41(6): 1047-1057
[14] 张忠良, 宋焕庭, 张丽梅, 等. 同一人不同年龄段的指纹特征信息变化[J]. 中国刑警学院学报, 2022, 3: 97-103
[15] Richmond S. Do fingerprint ridges and characteristics within ridges change with pressure?[J]. Australian Federal Police, Forensic Services, 2004, 5: 46-47
[16] 张致中, 张虎, 晁招相, 等. 新疆六个民族指纹白线的调查研究[J]. 遗传, 1994, 1: 5-7
[17] 阿布都艾尼, 艾琼华, 赛福鼎. 新疆伊犁维吾尔族、哈萨克族和蒙古族指纹白线正常值分析[J]. 解剖学杂志, 1997, 1: 77-80
[18] 熊继群, 石君. 湘西土家族、苗族、汉族指纹白线的研究[J]. 华夏医学, 2006, 2: 179-181
[19] 庄振西, 高秀珍. 辽宁满族和汉族指纹白线正常值分析[J]. 人类学学报, 1993, 3: 264-268
[20] 霍正浩, 彭亮, 陈银涛, 等. 宁夏汉族指纹白线正常值分析[J]. 中国优生与遗传杂志, 1998, 6: 133-135
[21] 全跃龙. 汉族指纹白线正常值分析[J]. 人类学学报, 1988, 2: 186-188
[22] Cherrill FR. Finger prints and disease[J]. Nature, 1950, 166(4223): 581-584
[23] David TJ, Ajdukiewicz AB, Read AE. Fingerprint changes in coeliac disease[J]. Br Med J, 1970, 4(5735): 594-596
[24] HIRSCH and Recke. Hautleisten und Krankheiten[M]. Berlin, Ernst-Reuter-Gesellschaft, 1971, 225-236
[25] Cannon M, Byrne M, Cotter D, et al. Further evidence for anomalies in the hand-prints of patients with schizophrenia: a study of secondary creases[J]. Schizophrenia Research, 1994, 13(2): 179-184
[26] Shakibaei F, Asadollahi GA, Tabibi A. Dermatoglyphics in patients with schizophrenia[J]. Journal of research in medical sciences: the official journal of Isfahan University of Medical Sciences, 2011, 16(8): 1055
[27] 甘子明, 徐兰. 精神分裂症患者的指纹白线和嵴线离解的研究[J]. 新疆医学院学报, 1995, 4: 215-218
[28] 陆国芳, 李树宁, 高丽荣, 等. 抑郁症患者的指纹类型及指纹白线[J]. 解剖学报, 2011, 42(5): 703-706
[29] 孙淑芳, 许振波, 韩向君, 等. 糖尿病患者指纹白线的分析[J]. 遗传, 1995, 2: 10-11
[30] Lee CK, Chang C, Johar A, et al. Fingerprint changes and verification failure among patients with hand dermatitis[J]. JAMA dermatology, 2013, 149(3): 294-299
[31] Li J, Glover JD, Zhang H, et al. Limb development genes underlie variation in human fingerprint patterns[J]. Cell, 2022, 185(1): 95-112
[32] 薄海玲. 指纹冲击线的识别与应用[D]. 长春: 吉林大学, 2004
[33] 欧阳常青. 手印鉴定中接合比对检验法的应用研究[J]. 中国司法鉴定, 2005, 4: 52-53+56
[34] Chauhan N, Soni M, Anand V, et al. Fingerprint classification using crease features[A]. In: 2016 IEEE Students’ Technology Symposium (TechSym)[C]. IEEE, 2016, 56-60
[35] Tadross RA, Badawi AM, Mahfouz MR, et al. Sex Determination from Fingerprint[J]. Cairo International Biomedical Engineering Conference, 2006, 6: 26-31
[36] Verma M, Agarwal S. Emilio C, Rodolfo Z, Paolo G, et al. Fingerprint based male-female classification[A]. In: Proceedings of the International Workshop on Computational Intelligence in Security for Information Systems CISIS’08[C]. Springer Berlin, Heidelberg, 2009, 251-257
[37] Richard Jonathan O. Taduran, et al. Sex determination from fingerprint ridge density and white line counts in Filipinos[J]. Homo, 2016, 67(2): 163-171
[38] Taura MG, Adamu LH, Asuku AY, et al. Adjacent digit fingerprint white line count differences: a pointer to sexual dimorphism for forensic application[J]. Egyptian Journal of Forensic Sciences, 2019, 9(1): 1-8
[39] Adamu LH, Asuku AY, Muhd UA, et al. Fingerprint White Line Counts: An Upcoming Forensic Tool for Sex Determination[J]. Arab Journal of Forensic Sciences & Forensic Medicine 2019, 1(9): 1165-1173
[40] Taura MG, Adamu LH, Asuku AY, et al. Quantity and asymmetry of fingerprint white lines: forensic implication[J]. Canadian Society of Forensic Science Journal, 2020, 53(1): 13-25
[41] 田润之, 赵雅彬. 基于指纹形态特征的人群年龄刻画研究[J]. 中国人民公安大学学报(自然科学版), 2023, 29(1): 11-20
[42] 李珍珍. 硅胶高仿指模的检验[J]. 刑事技术, 2021, 46(1): 91-95
[43] 蒋焕, 陈立宏, 李俐明, 等. 不同年龄阶段人的硅胶仿生指纹印泥痕迹特征[J]. 刑事技术, 2022, 47(4): 400-404
[44] GA/T 1533-2018,法庭科学指纹特征分类规范[S]
[45] HICKLIN A. Extended features under consideration[EB/OL]. https://www.nist.gov/system/files/documents/2016/12/19/p18_hicklin_extfpfeatures_2006-04.pdf. Released on:2006-03-31
[46] Jain AK, Chen Y, Demirkus M. Pores and ridges: High-resolution fingerprint matching using level 3 features[J]. IEEE transactions on pattern analysis and machine intelligence, 2006, 29(1): 15-27
[47] Science Working Group on Friction Ridge Analysis, Study and Technology. Standards for examining friction ridge impressions and resulting conclusions (latent/tenprint)[S/OL]. http://clpex.com/swgfast/documents/examinationsconclusions/111026_Examinations-Conclusions_1.0.pdf. Released on: 2005-01-13
[48] Vernon DSG. Automatic detection of secondary creases in fingerprints[J]. Optical Engineering, 1993, 32(10): 2616-2623
[49] 伍晨愉. 断纹检测及其在指纹识别中的应用研究[D]. 北京: 清华大学, 2003
[50] Wu C, Zhou J, Bian Z, et al. Robust crease detection in fingerprint images[A]. In: 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition[C]. IEEE, 2003, 2: II-505
[51] Zhou J, Wu C, Bian Z, et al. Improving fingerprint recognition based on crease detection[A]. In: ICBA. Biometric Authentication: First International Conference[C]. Springer Berlin Heidelberg, Biometric Authentication, 2004: 287-293
[52] Hymer P. Extraction and application of secondary crease information in fingerprint recognition systems[D]. Sweden: Link?ping University, 2005
[53] Zhou J, Chen F, Wu N, et al. Crease detection from fingerprint images and its applications in elderly people[J]. Pattern Recognition, 2009, 42(5): 896-906
[54] Laseinde OP. Analysis and detection of fingerprint creases[D]. America: West Virginia University, 2012
[55] Jian W, Zhou Y, Liu H, et al. Crease Detection and Repair Based on Minutia Density Distribution[A]. In: 2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN)[C]. IEEE, 2019, 446-451
[56] 吴迪, 高树辉, 张宁, 等. 光学相干层析技术在法庭科学领域的研究进展与应用展望[J]. 激光与光电子学进展, 2023, 60(12): 30-40
[57] Zam A, Dsouza R, Subhash HM, et al. Feasibility of Correlation Mapping Optical Coherence Tomography (cmOCT) for Anti-Spoof Sub-Surface Fingerprinting[J]. Journal of Biophotonics. 2013, 6(9): 663-667
[58] Ding B, Wang H, Chen P, et al. Surface and Internal Fingerprint Reconstruction From Optical Coherence Tomography through Convolutional Neural Network[J]. IEEE Transactions on Information Forensics and Security. 2021, 16: 685-700
[59] Zhang N, Wang C, Li Z, et al. Preliminary analysis of facial hair follicle distribution for forensic identification using OCT[A]. In: Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVI[C]. SPIE, 2018, 10497: 17-24
[60] 潘自勤. 指纹三级特征在指纹鉴定中的价值[J]. 刑事技术, 2014, 4: 45-47
[61] 卢有林, 刁龙珍, 曹丽姝. 对手指褶皱纹变化的研究[A]. 见:第一届全国手印专业学术交流会论文选[C]. 北京: 警官教育出版社, 1993, 81
[62] 赵雨涵. 可见指印阶段性特征研究[D]. 上海: 华东政法大学, 2021
[63] Reneau RD. Unusual latent print examinations[J]. Journal of Forensic Identification, 2003, 53(5): 531
[64] Davis LJ, Saunders CP, Hepler A, et al. Using subsampling to estimate the strength of handwriting evidence via score-based likelihood ratios[J]. Forensic science international, 2012, 216(1-3): 146-157
[65] Hepler AB, Saunders CP, Davis LJ, et al. Score-based likelihood ratios for handwriting evidence[J]. Forensic science international, 2012, 219(1-3): 129-140
[66] Meuwly D, Ramos D, Haraksim R. A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation[J]. Forensic science international, 2017, 276: 142-153
[67] 董锋, 赵雅彬, 罗亚平, 等. 似然比方法体系在法庭科学中的研究进展[J]. 证据科学, 2019, 27(3): 375-385
[68] Anthonioz A, Champod C. Integration of pore features into the evaluation of fingerprint evidence[J]. Journal of Forensic Sciences, 2014, 59(1): 82-93
[69] Jackson G, Black S. Use of data to inform expert evaluative opinion in the comparison of hand images-the importance of scars[J]. International Journal of Legal Medicine, 2014, 128: 555-563
[70] 吴春生, 李孝君, 吴浩. 基于深度学习的指纹自动识别技术[J]. 刑事技术, 2022, 47(1): 88-95
[71] 沈希忠, 吴迪. 基于YOLO的铝型材料表面小缺陷检测[J]. 浙江工业大学学报, 2022, 50(4): 372-380
[72] 吴萌萌, 张泽斌, 宋尧哲, 等. 基于自适应特征增强的小目标检测网络[J]. 激光与光电子学进展, 2023, 60(6): 65-72
[73] 高宝东. 基于YOLOv5的小目标检测算法与应用研究[D]. 银川: 宁夏大学, 2022
[74] 高梦婷, 孙晗, 唐云祁, 等. 基于改进YOLOv5的指纹二级特征检测方法[J]. 激光与光电子学进展, 2023, 60(10): 89-99
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