单次扫描连通域分析算法研究综述

doi:10.12263/DZXB.20210368

电子学报 ›› 2022, Vol. 50 ›› Issue (6): 1521-1536.DOI: 10.12263/DZXB.20210368

单次扫描连通域分析算法研究综述

曲立国¹^,², 陈国豪¹, 胡俊¹, 陈鹏¹

^1.安徽师范大学物理与电子信息学院, 安徽芜湖 241002
^2.安徽省智能机器人信息融合与控制实验室, 安徽芜湖 241002

收稿日期:2021-03-16 修回日期:2022-03-09 出版日期:2022-06-25
- 作者简介:
- 曲立国男，1979年出生，吉林舒兰人.安徽师范大学物理与电子信息学院副教授.主要研究方向为智能信息处理，检测技术与自动化装置．E-mail: qlg77@163.com
  陈国豪男，1997年出生，安徽池州人.安徽师范大学物理与电子信息学院硕士研究生.主要研究方向为计算机视觉与自动化装置． E-mail: cgh591614156@163.com
  胡俊男，1996年出生，安徽六安人.安徽师范大学物理与电子信息学院硕士研究生.主要研究方向为智能信息处理与自动化装置．E-mail: 17856939565@163.com
  陈鹏男，1975年出生，安徽萧县人．安徽师范大学物理与电子信息学院讲师.主要研究方向为机器学习．E-mail: ahnuchp@ahnu.edu.cn
- 基金资助:
- 安徽省高等学校自然科学研究项目重点项目 (KJ2019A0511)

A Review of Single-pass Connected Component Analysis Algorithms

QU Li-gou¹^,², CHEN Gou-hao¹, HU Jun¹, CHEN Peng¹

^1.School of Physics and Electronic Information, Anhui Normal University, Wuhu, Anhui 241002, China
^2.Anhui Provincial Engineering Laboratory on Information Fusion and Control of Intelligent Robot, Wuhu, Anhui 241002, China

Received:2021-03-16 Revised:2022-03-09 Online:2022-06-25 Published:2022-06-25
- Supported by:
- Natural Science Research Project Key Program of colleges and Universities in Anhui Province (KJ2019A0511)

摘要/Abstract

摘要：

连通域分析在单次扫描中标记像素同时提取每个连通域的特征数据，是二值图像处理的重要步骤之一.基于FPGA的硬件架构实现单次扫描连通域分析算法可以实现快速位流图像实时处理.本文重点分析了近十年来发展的连通域标记算法和单次扫描连通域分析算法，阐述了典型连通域分析算法的实现策略和框架，给出了它们的伪代码，并描述了它们的联合查找算法.此外，通过数据对比，从算法硬件架构的内存需求和吞吐量等方面对不同算法的性能进行了比较分析，并总结了它们的优缺点.分析结论为实现基于FPGA高速位流图像的连通域检测提供了理论依据和数据参考.

关键词: 连通域分析, 连通域标记, 特征提取, 图像处理, FPGA

Abstract:

Connected component analysis(CCA) is one of the major steps in binary image processing, which label pixels in single-pass and extract the features of each connected component at the same time. Single-pass connected component analysis algorithm based on FPGA hardware architecture can realize fast real-time bit stream image processing. In this article, we focus on connected component labeling(CCL) algorithms and single-pass connected component analysis algorithms developed in the last decade, explain the implementation strategies and architectures of the typical connected component analysis algorithms, present their pseudo codes, and describe their Union-find algorithms. In addition, through data comparison, the performance of different algorithms is compared and analyzed in terms of memory requirements and throughput of algorithm hardware architectures, and their advantages and disadvantages are summarized. The analysis results provide a theoretical basis and data reference for the realization of connected component detection based on FPGA high-speed bit stream images.

Key words: connected component analysis, connected component labeling, feature extraction, image processing, FPGA

中图分类号:

TP211

曲立国, 陈国豪, 胡俊, 陈鹏. 单次扫描连通域分析算法研究综述[J]. 电子学报, 2022, 50(6): 1521-1536.

QU Li-gou, CHEN Gou-hao, HU Jun, CHEN Peng. A Review of Single-pass Connected Component Analysis Algorithms[J]. Acta Electronica Sinica, 2022, 50(6): 1521-1536.

图/表 15

图1 四连通和八连通

图2 连通域示例和联合查找树数据结构F

表1 典型CCL和CCA算法的性能比较

算法缩写	形式	扫描单元	标记单元	连通性	运行时间复杂度	等价关系解析策略	是否标签重用
OCL^[10]	Two-pass CCL	Pixel	Pixel	8	—	Rosenfeld	—
SCL^[14]	Multi-pass CCL	Pixel	Pixel	8	Linear	Iterative connection table	—
CT^[15]	Two-pass CCL	Pixel	Pixel	8	Linear	None	—
CTCL^[22]	Two-pass CCL	Pixel	Pixel	8	Linear	Equivalent label set	—
ICTCL^[23]	Two-pass CCL	Pixel	Pixel	8	Linear	Equivalent label set	—
RCL^[24]	Two-pass CCL	Run	Run	8	Linear	Equivalent label set	—
BCL^[26]	Two-pass CCL	Block	Block	8	Linear	QuickUnion+path compression	—
OSP^[42]	Single-pass CCA	Pixel	Pixel	8	Linear	Context-based union-find	No
IOSP^[45]	Single-pass CCA	Pixel	Pixel	8	Linear	Context-based+relabeling	Yes
SLSP^[48]	Single-pass CCA	Pixel	Pixel	8	Linear	Context-based union-find	Yes
DLSP^[50]	Single-pass CCA	Pixel	Run	8	Linear	Context-based union-find	Yes
ZZSP^[51]	Single-pass CCA	Pixel	Run	8	Linear	Context-based union-find	Yes
TRLE^[52]	Single-pass CCA	Run	Run	8	—	QuickUnion	Yes
ZRSP^[53]	Single-pass CCA	Pixel	Run	4	Linear	Multi-layer-index structure	Yes
TRSP^[54]	Single-pass CCA	Run	Run	4	Linear	Linked list	Yes
CSP^[56]	Single-pass CCA	Cell	Cell	4	Linear	Relabeling memory	Yes
JSP^[58]	Single-pass CCA	Pixel	Pixel	8	Linear	None	Yes

图3 CCL和CCA算法的扫描窗口

图4 CTCL和ICTCL算法的扫描窗口

图5 OSP算法的架构

图6 两种合并模式

图7 TRSP算法概述

图8 Next, Head和Tail指针的用法

图9 JSP算法的硬件架构,其中红线表示S1的输入和输出

表2 不同单次扫描CCA架构对于W×H大小图像的内存需求

缩写对应描述	缩写	OSP^[42]	IOSP^[45]	SLSP^[48]	DLSP^[50]	ZZSP^[51]	TRSP^[54]	JSP^[58]
Number of label	N_L	$W × H 4$	$W 2$	$W + 5 2$	$W + 5 2$	$W 2$	$W 2$	$W × H 4$
Nunber of merge	N_M	$W - 1 2$	$W - 1 2$	$W - 1 2$	$W - 1 2$	—	—	—
Row buffer	RB	$W L × W$	$W L × W$	$W L × W$	$W L × W$	$W L × W$	$2 × W$	$W L × W$
Merge table	MT	$W L × N L$	$2 W L × N L$	$W A L × N L$	$W A L × N L$	$W A L × N L$	—	—
Data table	DT	$W D × N L$	$2 W D × N L$	$W D × N L$	$W D × N L$	$W D × N L$	$W D × N L$	$W D × N L$
Chain stack	S	$2 W L × N M$	$2 W L × N M$	$2 W L × N M$	$2 W L × N M$	—	—	—
Recycle FIFO	FIFO	—	—	$W L × N L$	$W L × N L$	$W L × N L$	—	$W L × N L$
Translation table	TT	—	$W L × N L$	—	—	—	—	—
Stale label stack	SLS	—	—	$W L × W 10$	—	—	—	—
Valid tag	V	—	—	$N L$	—	—	—	—
Active tag	AT	—	—	$2 × N L$	$2 × N L$	$l o g 2 W + 1 × N L$	—	—
Linked list	List	—	—	—	—	—	$3 W L × N L$	—
Zig-Zag buffer	ZZ	—	—	—	—	$W$	—	—

表2 不同单次扫描CCA架构对于W×H大小图像的内存需求

缩写对应描述	缩写	OSP^[42]	IOSP^[45]	SLSP^[48]	DLSP^[50]	ZZSP^[51]	TRSP^[54]	JSP^[58]
Number of label	N_L	$W × H 4$	$W 2$	$W + 5 2$	$W + 5 2$	$W 2$	$W 2$	$W × H 4$
Nunber of merge	N_M	$W - 1 2$	$W - 1 2$	$W - 1 2$	$W - 1 2$	—	—	—
Row buffer	RB	$W L × W$	$W L × W$	$W L × W$	$W L × W$	$W L × W$	$2 × W$	$W L × W$
Merge table	MT	$W L × N L$	$2 W L × N L$	$W A L × N L$	$W A L × N L$	$W A L × N L$	—	—
Data table	DT	$W D × N L$	$2 W D × N L$	$W D × N L$	$W D × N L$	$W D × N L$	$W D × N L$	$W D × N L$
Chain stack	S	$2 W L × N M$	$2 W L × N M$	$2 W L × N M$	$2 W L × N M$	—	—	—
Recycle FIFO	FIFO	—	—	$W L × N L$	$W L × N L$	$W L × N L$	—	$W L × N L$
Translation table	TT	—	$W L × N L$	—	—	—	—	—
Stale label stack	SLS	—	—	$W L × W 10$	—	—	—	—
Valid tag	V	—	—	$N L$	—	—	—	—
Active tag	AT	—	—	$2 × N L$	$2 × N L$	$l o g 2 W + 1 × N L$	—	—
Linked list	List	—	—	—	—	—	$3 W L × N L$	—
Zig-Zag buffer	ZZ	—	—	—	—	$W$	—	—

表3 OSP和JSP算法架构对不同分辨率图像的内存需求比较

图像大小	VGA	DVD	HD720	HD1080	UHD3K	UHD4K	UHD8K
图像大小	640×480	720×576	1 280×720	1 920×1 080	3 840×2 160	4 096×2 160	7 680×4 320
N_L	76 800	103 680	230 400	518 400	2 073 600	2 211 840	8 294 400
N_M	319	359	639	959	1 919	2 047	3 839
W_L	17	17	18	19	22	22	23
W_D	57	59	62	65	72	72	77
OSP^[48]
S	10 846	12 206	23 004	36 442	84 436	90 068	176 594
RB	10 880	12 240	23 040	36 480	84 480	90 112	176 640
MT	1 305 600	1 762 560	4 147 200	9 849 600	45 619 200	48 660 480	190 771 200
DT	4 377 600	6 117 120	14 284 800	33 696 000	149 299 200	159 252 480	638 668 800
Total	5 704 926	7 904 126	18 478 044	43 618 522	195 087 316	208 093 140	829 793 234
JSP^[58]
RB	10 880	12 240	23 040	36 480	84 480	90 112	176 640
FIFO	1 305 600	1 762 560	4 147 200	9 849 600	45 619 200	48 660 480	190 771 200
DT	4 377 600	6 117 120	14 284 800	33 696 000	149 299 200	159 252 480	638 668 800
Total	5 694 080	7 891 920	18 455 040	43 582 080	195 002 880	208 003 072	829 616 640

图10 几种CCA算法处理不同分辨率图像的内存位数比较

表4 几种CCA硬件架构的比较

硬件架构	采用设备	图像大小/pixel	特征提取^a	LUTs	寄存器	BRAM /bit	Fmax/MHz	吞吐量/ (Mpixel/s)
SLSP^[48]	Kintex 7	256×256	BB	493	296	108K	185.59	154.50
ZZSP^[51]	Kintex 7	256×256	BB+A	882	503	18K	220.02	220.02
TRSP^[54]	Virtex 2	256×256	BB	547	183	72K	104.26	104.26
OSP^[42]	Spartan 2	640×480	A,N	810	286	16K	—	—
IOSP^[45]	Virtex 2	640×480	A,N	1 757	600	72K	40.64	38.25
TRSP^[54]	Virtex 2	640×480	BB	654	227	92K	97.07	97.07
JSP^[58]	Cyclone 4	640×480	BB+C	36 478	—	18K	60.58	60.58

图11 造成最差吞吐量的图案

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单次扫描连通域分析算法研究综述

A Review of Single-pass Connected Component Analysis Algorithms

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