Research on Fast Multi-Threshold Image Segmentation Technique Using Histogram Analysis

被引:9
作者
Xu, Mingjin [1 ]
Chen, Shaoshan [2 ]
Gao, Xiaopeng [1 ]
Ye, Qing [1 ]
Ke, Yongsheng [1 ]
Huo, Cong [1 ]
Liu, Xiaohong [1 ]
机构
[1] Naval Univ Engn, Coll Naval Architecture & Ocean Engn, Wuhan 430033, Peoples R China
[2] Xichang Satellite Launch Ctr, Wenchang 571300, Peoples R China
关键词
multi-threshold segmentation; OTSU algorithm; histogram; curve extremum method; PERFORMANCE; ALGORITHM; ENTROPY;
D O I
10.3390/electronics12214446
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper investigates a method for the multi-threshold segmentation of grayscale imaging using the local minimum points of a histogram curve as the segmentation threshold. By smoothing the histogram curve and judging the conditions, the expected peaks and valleys are identified, and the corresponding minimum points are used as segmentation thresholds to achieve fast multi-threshold image segmentation. Compared to the OTSU method (maximum between-class variance) for multi-threshold segmentation and the region growing method, this method has less computational complexity. In the recognition and segmentation process of solder pads with adhesion of underfill in LED Chips, the segmentation time is less than one percent of that of the OTSU method and the region growing method. The segmentation effect is better than the OTSU method and the region growing method, and it can achieve fast multi-threshold segmentation of images. Moreover, it has strong adaptability to the differences in the overall grayscale of images, meeting the requirements for high UPH (Units Per Hour) in industrial production lines.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] An Improved Otsu Multi-threshold Image Segmentation Algorithm Based on Pigeon-Inspired Optimization
    Liu, Wei
    Shi, Heng
    Pan, Shang
    Huang, Yongkun
    Wang, Yingbin
    2018 11TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2018), 2018,
  • [22] An Adaptive Bi-Mutation-Based Differential Evolution Algorithm for Multi-Threshold Image Segmentation
    Sun, Yu
    Yang, Yingying
    APPLIED SCIENCES-BASEL, 2022, 12 (11):
  • [23] Infrared image multi-threshold segmentation algorithm based on improved pulse coupled neural networks
    Kong, XW
    Huang, J
    Shi, H
    JOURNAL OF INFRARED AND MILLIMETER WAVES, 2001, 20 (05) : 365 - 369
  • [24] Otsu Multi-Threshold Image Segmentation Based on Adaptive Double-Mutation Differential Evolution
    Guo, Yanmin
    Wang, Yu
    Meng, Kai
    Zhu, Zongna
    BIOMIMETICS, 2023, 8 (05)
  • [25] Road Target Detection Based on Otsu Multi-Threshold Segmentation
    Li, Hui-Guang
    Lu, Chang-Yong
    Qi, Long
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING AND CONTROL SYSTEMS (MECS2015), 2016, : 265 - 269
  • [26] Two-dimensional Otsu multi-threshold image segmentation based on hybrid whale optimization algorithm
    Ning, Guiying
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (10) : 15007 - 15026
  • [27] Multi-Threshold Image Segmentation of Maize Diseases Based on Elite Comprehensive Particle Swarm Optimization and Otsu
    Chen, Chengcheng
    Wang, Xianchang
    Heidari, Ali Asghar
    Yu, Helong
    Chen, Huiling
    FRONTIERS IN PLANT SCIENCE, 2021, 12
  • [28] An improved weighted mean of vectors optimizer for multi-threshold image segmentation: case study of breast cancer
    Hao, Shuhui
    Huang, Changcheng
    Heidari, Ali Asghar
    Chen, Huiling
    Liang, Guoxi
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2024, 27 (10): : 13945 - 14004
  • [29] Fingerprint image segmentation based on multi-features histogram analysis
    Wang, Peng
    Zhang, Youguang
    MIPPR 2007: AUTOMATIC TARGET RECOGNITION AND IMAGE ANALYSIS; AND MULTISPECTRAL IMAGE ACQUISITION, PTS 1 AND 2, 2007, 6786
  • [30] Image Multi-Threshold Segmentation Based on Variable Precision Rough Set and K-L Roughness Particle Swarm Optimization
    She, Zhiyong
    Song, Tao
    Zhang, Dongpo
    Feng, Yueping
    TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2025, 32 (02): : 704 - 712