Advanced Search
Volume 40 Issue 1
Jan.  2018
Turn off MathJax
Article Contents
QU Zhiguo, TAN Xiansi, LIN Qiang, WANG Hong, FEI Taiyong. Randomized Wide Line Detector[J]. Journal of Electronics & Information Technology, 2018, 40(1): 209-218. doi: 10.11999/JEIT170296
Citation: QU Zhiguo, TAN Xiansi, LIN Qiang, WANG Hong, FEI Taiyong. Randomized Wide Line Detector[J]. Journal of Electronics & Information Technology, 2018, 40(1): 209-218. doi: 10.11999/JEIT170296

Randomized Wide Line Detector

doi: 10.11999/JEIT170296
Funds:

The National Natural Science Foundation of China (61401504), China Postdoctoral Science Foundation (2014M 562562)

  • Received Date: 2017-04-05
  • Rev Recd Date: 2017-11-06
  • Publish Date: 2018-01-19
  • To eliminate computation redundancy and improve speed of the basic wide line detector, a fast implementation, named randomized moving wide line detector, is proposed. Instead of moving the mask pixel by pixel to detect wide lines as did in the basic implementation, the randomized moving wide line detector places the mask in the image randomly, and then determines the mask moving strategy heuristically according to the current pixel. In this way, the mask moving is accelerated, leading to obvious decrease of computational redundancy in the basic detector. Furthermore, two early termination conditions are proposed to break out of the detecting loop based on the detection situation of wide lines. Testing images are adopted for performance evaluation of the randomized moving wide line detector. Experimental results demonstrate that the proposed detector accelerates the basic wide line detector significantly while keeping its detection performance unaffected.
  • loading
  • LINDEBERG T. Edge detection and ridge detection with automatic scale selection[J]. International Journal of Computer Vision, 1998, 30(2): 117-154. doi: 10.1023/A: 1008097225773.
    JACOB M and UNSER M. Design of steerable filters for feature detection using Canny-Like criteria[J]. IEEE Transaction on Pattern Analysis Machine Intelligence, 2004, 26(8): 1007-1019. doi: 10.1109/TPAMI.2004.44.
    EBERLY D, GARDNER R, MORSE B, et al. Ridges for image analysis[J]. Journal of Mathematical Imaging and Vision, 1994, 4(4): 353-373. doi: 10.1007/BF01262402.
    AGGARWAL N and KARL W C. Line detection in images through regularized Hough transform[J]. IEEE Transactions on Image Processing, 2006, 15(3): 582-591. doi: 10.1109/TIP. 2005.863021.
    XU Zezhong, SHIN Bok Suk, and KLETTE Reinhard. Closed form line-segment extraction using the Hough transform[J]. Pattern Recognition, 2015, 48(12): 4012-4023. doi: 10.1016/j. patcog.2015.06.008.
    LOPEZ-MOLINA C, VIDAL-DIEZ DE ULZURRUN G, BAETENS J M, et al. Unsupervised ridge detection using second order anisotropic Gaussian kernels[J]. Signal Processing, 2015, 116: 55-67. doi: 10.1016/j.sigpro.2015.03. 024.
    HU Yangyang, ZHANG Wenqiang, LU Hong, et al. Wide line detection with water flow[C]. 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shenzhen, 2016: 1353-1355.
    PANDEY D, YIN Xiaoxia, WANG Hua, et al. Accurate vessel segmentation using maximum entropy incorporating line detection and phase-preserving denoising[J]. Computer Vision and Image Understanding, 2017, 155: 162-172. doi: 10.1016/j.cviu.2016.12.005.
    SUDESHNA S K and SANTI P M. Retinal blood vessel extraction using tunable bandpass filter and fuzzy conditional entropy[J]. Computer Methods and Programs in Biomedicine, 2016, 133: 111-132. doi: 10.1016/j.cmpb.2016. 05.015.
    LI Shuxiao, CHANG Hongxing, and ZHU Chengfei. Fast curvilinear structure extraction and delineation using density estimation[J]. Computer Vision and Image Understanding, 2009, 113(6): 763-775. doi: 10.1016/j.cviu.2009.01.003.
    LIU L, ZHANG D, and YOU J. Detecting wide lines using isotropic nonlinear filtering [J]. IEEE Transactions on Image Processing, 2007, 16(6): 1584-1595. doi: 10.1109/TIP.2007. 894288.
    LIU L, NGADI M O, PRASHER S O, et al. Objective determination of pork marbling scores using the wide line detector[J]. Journal of Food Engineering, 2012, 110: 497-504. doi: 10.1016/j.jfoodeng.2011.11.008.
    CRISTIAN V and SERGIU N. Detecting curvilinear featuresusing structure tensors[J]. IEEE Transactions on Image Processing, 2015, 24(11): 3874-3887. doi: 10.1109/TIP. 2015.2447451.
    SMITH S M and BRADY J M. SUSANA new approach to low level image processing[J]. International Journal of Computer Vision, 1997, 23(1): 45-78. doi: 10.1023/A: 1007963824710.
    KNUTH D E, MORRIS J H, and PRATT V R. Fast pattern matching in strings[J]. SIAM Journal of Computing, 1977, 6: 323-350. doi: 10.1137/0206024.
    BOYER R S and MOORE J S. A fast string searching algorithm[J]. Communications of the ACM, 1977, 20(10): 762-772. doi: 10.1145/359842.359859.
    ABDOU I E and PRATT W K. Quantitative design and evaluation of enhancement/thresholding edge detectors[J]. Proceedings of the IEEE, 1979, 67(5): 753-763. doi: 0.1109/ PROC.1979.11325.
    IGOR S and ALEKSEJ A. Convolutional neural network based automatic object detection on aerial images[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 14(5): 740-744. doi: 10.1109/LGRS.2016.2542358.
    RODRIGO F N, ROBERTO A L, and RUBENS C M. Fingerprint liveness detection using convolutional neural networks[J]. IEEE Transactions on Information Forensics and Security, 2016, 11(6): 1206-1213. doi: 10.1109/TIFS. 2016.2520880.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (894) PDF downloads(155) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return