Quick automatic head image matting method based on segmentation and propagation

被引:0
|
作者
Wang, Xiaofan [1 ]
Li, Shengjie [1 ]
Sui, Liansheng [1 ]
Wang, Jiahao [1 ]
机构
[1] Xian Univ Technol, Sch Comp Sci & Technol, 5 Jinhua South Rd, Xian 710048, Peoples R China
关键词
Image matting; Image segmentation; Gray level; Propagation method; Contour extraction;
D O I
10.1016/j.patrec.2019.02.012
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image matting is a process of extracting objects from background in an image, which is an important work in digital image processing and video editing. Previous methods have poor performance and most methods need trimap or scribble to compute to get accurate image matting results. In this paper a quick automatic head image matting method for certificate photo production is put forward, which could rapidly extract satisfied head photo from images that are shoot by portable camera. First a new training data set about hair matting is created, and the image is segmented into different regions according to different gray level; then we detect and locate the face and eyes to adjust the correct head position; Finally, the accurate hair pixels are extracted from the edge region around head by multimodal Gaussian process regression. It's the advantage that the regions with clear foreground and background could be quickly extracted by segmented method, and the regions with similar foreground and background colors or complicated textures were labeled (the edge regions with hair around head), thus the hair could be extracted in smaller area. In our method the quick and accurate extracting of head photo needn't the trimap or scribbling or lots of training. Experimental results clearly demonstrate the superiority of our algorithm over previous methods. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:30 / 37
页数:8
相关论文
共 50 条
  • [1] An automatic method for image matting based on saliency detection
    College of Computer Science and Electronic Engineering, Hunan University, Changsha, China
    J. Comput. Inf. Syst., 10 (3571-3578): : 3571 - 3578
  • [2] Automatic blur region segmentation approach using image matting
    Zhao, Jufeng
    Feng, Huajun
    Xu, Zhihai
    Li, Qi
    Tao, Xiaoping
    SIGNAL IMAGE AND VIDEO PROCESSING, 2013, 7 (06) : 1173 - 1181
  • [3] Automatic blur region segmentation approach using image matting
    Jufeng Zhao
    Huajun Feng
    Zhihai Xu
    Qi Li
    Xiaoping Tao
    Signal, Image and Video Processing, 2013, 7 : 1173 - 1181
  • [4] Iterative transductive learning for automatic image segmentation and matting with RGB-D data
    He, Bei
    Wang, Guijin
    Zhang, Cha
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2014, 25 (05) : 1031 - 1043
  • [5] Automatic image segmentation by wave propagation
    Porikli, F
    IMAGE PROCESSING: ALGORITHMS AND SYSTEMS III, 2004, 5298 : 536 - 543
  • [6] Automatic grayscale image segmentation based on Affinity Propagation clustering
    Zhou, Shibing
    Xu, Zhenyuan
    PATTERN ANALYSIS AND APPLICATIONS, 2020, 23 (01) : 331 - 348
  • [7] Automatic grayscale image segmentation based on Affinity Propagation clustering
    Shibing Zhou
    Zhenyuan Xu
    Pattern Analysis and Applications, 2020, 23 : 331 - 348
  • [8] Deep Interactive Image Matting With Feature Propagation
    Ding, Henghui
    Zhang, Hui
    Liu, Chang
    Jiang, Xudong
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 31 : 2421 - 2432
  • [9] Automatic and Accurate Image Matting
    Hu, Wu-Chih
    Huang, Deng-Yuan
    Yang, Ching-Yu
    Jhu, Jia-Jie
    Lin, Cheng-Pin
    COMPUTATIONAL COLLECTIVE INTELLIGENCE: TECHNOLOGIES AND APPLICATIONS, PT III, 2010, 6423 : 11 - +
  • [10] Automatic Image Matting Using Component-Hue-Difference-Based Spectral Matting
    Hu, Wu-Chih
    Hsu, Jung-Fu
    INTELLIGENT INFORMATION AND DATABASE SYSTEMS (ACIIDS 2012), PT II, 2012, 7197 : 148 - 157