Lip segmentation using automatic selected initial contours based on localized active contour model

被引:4
|
作者
Lu, Yuanyao [1 ]
Liu, Qingqing [1 ]
机构
[1] North China Univ Technol, Sch Elect & Informat Engn, 5 Jinyuanzhuang Rd, Beijing 100144, Peoples R China
基金
中国国家自然科学基金; 北京市自然科学基金;
关键词
Lip segmentation; Localized active contour model; Initial contour; Illumination equalization; Color space; IMAGE SEGMENTATION; EXTRACTION; SNAKES;
D O I
10.1186/s13640-017-0243-9
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
With the rapid development of artificial intelligence and the increasing popularity of smart devices, human-computer interaction technology has become a multimedia and multimode technology from being computer-focused to people-centered. Among all ways of human-computer interactions, using language to interact with machines is the most convenient and efficient one. However, the performance of audio speech recognition systems is not satisfied in a noisy environment. Thus, more and more researchers focus their works on visual lip reading technology. By extracting lip movement features of speakers rather than audio features, visual lip reading systems can get superior results when noises and interferences exist. Lip segmentation plays an important role in a visual lip reading system, since the segmentation result is crucial to the final recognition accuracy. In this paper, we propose a localized active contour model-based method using two initial contours in a combined color space. We apply illumination equalization to original RGB images to decrease the interference of uneven illumination. A combined color space consists of the U component in CIE-LUV color space and the sum of C2 and C3 components of the image after discrete Hartley transform. We select a rhombus as the initial contour of a closed mouth, because it has a similar shape to a closed lip. For an open mouth, we utilize a combined semi-ellipse as the initial contours of both outer and inner lip boundaries. After attaining the results of each color component separately, we merge them together to obtain the final segmentation result. From the experiment, we can conclude that this method can get better segmentation results compared with the method using a circle as the initial contour to segment gray images and images in combined color space, especially for open mouth. An extremely obvious advantage of this method is the results of open mouth excluding internal information of mouth such as teeth, black holes, and tongue, because of the introduction of the inner initial contour.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Lip segmentation using automatic selected initial contours based on localized active contour model
    Yuanyao Lu
    Qingqing Liu
    [J]. EURASIP Journal on Image and Video Processing, 2018
  • [2] Lip segmentation using localized active contour model with automatic initial contour
    Lu, Yuanyao
    Zhou, Tenghe
    [J]. NEURAL COMPUTING & APPLICATIONS, 2018, 29 (05): : 1417 - 1424
  • [3] Retraction Note: Lip segmentation using localized active contour model with automatic initial contour
    Yuanyao Lu
    Tenghe Zhou
    [J]. Neural Computing and Applications, 2024, 36 (18) : 11039 - 11039
  • [4] A Study of Active Contour Segmentation Models Based on Automatic Initial Contour
    Bo, Cai
    Liu, Zhigui
    Wang, Junbo
    Zhu, Yuyu
    [J]. International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8 (04): : 201 - 214
  • [5] The study of automatic initial contour in active contour based segmentation models
    Cai, Bo
    Liu, Zhigui
    Wang, Junbo
    Zhu, Yuyu
    [J]. Journal of Computational Information Systems, 2015, 11 (17): : 6119 - 6127
  • [6] Automatic segmentation of lizard spots using an active contour model
    Heriberto Giraldo-Zuluaga, Jhony
    Enrique Salazar-Jimenez, Augusto
    [J]. REVISTA FACULTAD DE INGENIERIA-UNIVERSIDAD DE ANTIOQUIA, 2016, (79): : 33 - 40
  • [7] Automatic lip tracking:: Bayesian segmentation and active contours in a cooperative scheme
    Liévin, M
    Delmas, P
    Coulon, PY
    Luthon, F
    Fristot, V
    [J]. IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS, PROCEEDINGS VOL 1, 1999, : 691 - 696
  • [8] Automatic segmentation of the lungs using multiple active contours and outlier model
    Silveira, Margarida
    Marques, Jorge
    [J]. 2006 28TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-15, 2006, : 4501 - +
  • [9] Automatic segmentation of cell nuclei using Krill Herd optimization based multi-thresholding and Localized Active Contour Model
    Beevi, Sabeena K.
    Nair, Madhu S.
    Bindu, G. R.
    [J]. BIOCYBERNETICS AND BIOMEDICAL ENGINEERING, 2016, 36 (04) : 584 - 596
  • [10] Initial Contour Automatic Selection of Geometric Active Contour Model
    Dang, Hongshe
    Hong, Ying
    Fang, Xin
    Qiang, Feili
    [J]. ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL II, PROCEEDINGS, 2009, : 66 - 69