基于群智能的图书馆人脸识别系统关键技术

doi:10.13229/j.cnki.jdxbgxb20210416

摘要/Abstract

摘要：

为了促进图书馆向智慧新形态的转变，本文针对人脸识别中的图像分割技术，首先提出了一种混合连续蚁群优化算法（BACO），并进一步提出了一种基于BACO的多阈值图像分割模型用于面部图像分割。为了验证基于BACO的多阈值图像分割模型的性能，将其与其他9种同类方法进行了比较实验。针对获得的实验结果，首先使用PSNR和FSIM对分割结果进行了评估，然后采用Wilcoxon符号秩检验对评估进行了进一步的分析。所得到的结果清楚地证实了基于BACO的多阈值图像分割模型获得了最优的表现。因此，提出的多阈值图像分割模型可为下一步的面部识别乃至智慧图书馆的建设奠定基础。

关键词: 智慧图书馆, 图像分割, 群智能优化, 人脸识别

Abstract:

In order to facilitate the transformation of libraries to new forms of smart libraries， face recognition plays a very important role in it. Image segmentation， on the other hand， is one of the most fundamental studies in face recognition. In this study， we first propose a hybrid successive ant colony optimization algorithm （BACO）， and further propose a BACO-based multi-threshold image segmentation model for facial image segmentation. In order to verify the performance of the BACO-based multi-threshold image segmentation model， it is compared with nine other similar methods for experiments. For the obtained experimental results， the segmentation results were first evaluated using PSNR and FSIM， and the evaluation was further analyzed using Wilcoxon signed-rank test. The obtained results clearly confirm that the BACO-based multi-threshold image segmentation model obtains the optimal performance. Thus， the proposed multi-threshold image segmentation model lays a solid foundation for the next step of facial recognition and even smart library construction.

Key words: smart library, image segmentation, swarm intelligence optimization, face recognition

中图分类号:

TP391

汤松梅. 基于群智能的图书馆人脸识别系统关键技术[J]. 吉林大学学报(工学版), 2021, 51(6): 2216-2224.

Song-mei TANG. Key technology of face recognition system based on swarm intelligence in library[J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(6): 2216-2224.

图/表 7

图1

图2

图3

表1

两个评价指标的定义和说明"

名称	峰值信噪比（PSNR）	特征相似度指数（FSIM）
公式	$P S N R = 20 ? l o g 10 ? 255 R M S E$	$F S I M = ∑ I ∈ Ω S L X P C m X ∑ I ∈ Ω P C m X$
描述	评估分割后的图像与原始图像之间的差异。	定义质量分数，它反映了一个地方结构的重要性。

表1

表2

表3

图4

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阈值水平	~	BACO	SMA	ACOR	WOA	CS	ABC	SCA	MVO	HHO
	+/-/=	~	1/1/2	0/0/4	1/0/3	3/0/1	3/0/1	2/0/2	1/0/3	2/1/1
3	排序均值	2	3.75	3	6.5	7.25	6.25	7	3	6.25
	排名	1	4	2	7	9	5	8	2	5
	+/-/=	~	1/0/3	0/0/4	3/0/1	2/0/2	2/0/2	4/0/0	1/0/3	2/0/2
4	排序均值	2	5	3.25	6	5.5	4	8.5	3	7.75
	排名	1	5	3	7	6	4	9	2	8
	+/-/=	~	1/0/3	0/0/4	2/0/2	2/0/2	3/0/1	4/0/0	1/0/3	3/0/1
5	排序均值	2.25	4.5	3	7	4.75	3.75	8.75	3	8
	排名	1	5	2	7	6	4	9	2	8
	+/-/=	~	2/0/2	0/0/4	1/0/3	3/0/1	0/0/4	4/0/0	3/0/1	4/0/0
13	排序均值	2	4	2.25	5.25	5.25	2.75	9	6.5	8
	排名	1	4	2	5	5	3	9	7	8
	+/-/=	~	3/0/1	0/0/4	3/0/1	3/0/1	2/0/2	4/0/0	4/0/0	4/0/0
14	排序均值	1.25	4.25	2.5	5	4.75	3.5	9	7	7.75
	排名	1	4	2	6	5	3	9	7	8
	+/-/=	~	1/0/3	0/0/4	2/0/2	2/0/2	0/0/4	4/0/0	2/0/2	4/0/0
15	排序均值	1.75	3.25	3.25	4.5	5.5	3.25	9	6.5	8
	排名	1	2	2	5	6	2	9	7	8

阈值水平	~	BACO	SMA	ACOR	WOA	CS	ABC	SCA	MVO	HHO
	+/-/=	~	1/0/3	0/0/4	2/0/2	2/0/2	2/0/2	4/0/0	1/0/3	2/0/2
3	排序均值	1.75	3	3	6	7	5.25	9	3.25	6.75
	排名	1	2	2	6	8	5	9	4	7
	+/-/=	~	1/0/3	0/0/4	3/0/1	3/0/1	2/0/2	4/0/0	2/0/2	2/0/2
4	排序均值	1	5.25	2.5	7.5	5.75	4.75	9	3.5	5.75
	排名	1	5	2	8	6	4	9	3	6
	+/-/=	~	1/1/2	0/0/4	3/0/1	3/0/1	2/0/2	4/0/0	1/0/3	2/0/2
5	排序均值	2.5	3	2.75	6.5	7	4.75	9	3.25	6.25
	排名	1	3	2	7	8	5	9	4	6
	+/-/=	~	1/0/3	1/0/3	2/0/2	2/0/2	1/0/3	4/0/0	4/0/0	4/0/0
13	排序均值	1.25	4.25	2.5	5.25	5.75	2.75	9	6.5	7.75
	排名	1	4	2	5	6	3	9	7	8
	+/-/=	~	3/0/1	0/0/4	2/0/2	3/0/1	2/0/2	4/0/0	4/0/0	4/0/0
14	排序均值	1.5	4.25	2.25	5	5	3.25	9	7	7.75
	排名	1	4	2	5	5	3	9	7	8
	+/-/=	~	2/0/2	0/0/4	3/0/1	4/0/0	1/0/3	4/0/0	4/0/0	4/0/0
15	排序均值	1.75	3.25	3.25	4.5	5.5	3.25	9	6.5	8
	排名	1	2	2	5	6	2	9	7	8