赵浩钧,林川,陈海杰,张玉薇

• 1:广西科技大学电气与信息工程学院

摘要(Abstract)：

作为目标识别的关键步骤,轮廓检测已成为计算机视觉研究领域的热点之一.仿生学研究发现,在初级视皮层(V1)细胞中,驱动彩色亮度单元的双拮抗细胞感受野对亮度和颜色信息敏感且具有方向选择性,对于轮廓检测起到重要作用.本文提出一种基于颜色拮抗和纹理抑制的轮廓检测模型,通过二维高斯差分DOG函数来模拟纹理抑制模板,对不同的双拮抗细胞通道进行纹理抑制,在基于颜色拮抗特性检测模型中考虑了抑制纹理的作用.实验结果表明:在BSDS300图像库下本文模型在纹理抑制方面较现有模型有一定的优势,能够较好的提取目标轮廓,是颜色拮抗目标轮廓检测模型中的一种新思路.

关键词(KeyWords)： 颜色拮抗;轮廓检测;纹理抑制

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金资助项目(61866002);; 广西自然科学基金项目(2018GXNSFAA138122,2015GXNSFAA139293);; 广西研究生教育创新计划项目(YCSW2018203);; 广西科技大学研究生教育创新计划项目(GKYC201706,GKYC201803);; 2018广西大学生创新创业训练计划项目(201810594072);; 广西高等学校科学研究项目(KY2015LX173)资助

作者(Author): 赵浩钧,林川,陈海杰,张玉薇

DOI: 10.16375/j.cnki.cn45-1395/t.2018.04.002

参考文献(References)：

• [1]俞昊,林川,谭光兴,等.视觉注意机制与Canny算子结合的目标轮廓检测方法[J].广西科技大学学报,2016,27(2):87-92.
• [2]闫夏,谭光兴,林川.基于免疫聚类算法的MRI膝关节图像分割[J].广西科技大学学报,2015,26(1):70-74.
• [3] LAGUNOVSKY D,ABLAMEYKO S. Fast line and rectangle detection by clustering and grouping[M]. Berlin:Berlin Heidel‐berg Springer,1997.
• [4] SHPANER M, MOLHOLM S, FORDE E, et al. Disambiguating the roles of area V1 and the lateral occipital complex(LOC)in contour integration[J]. Neuroimage,2013,69(4):146-156.
• [5] GRIGORESCU C,PETKOV N,WESTENBERG M a. Contour detection based on nonclassical receptive field inhibition[J].IEEE Transactions on Image Processing a Publication of the IEEE Signal Processing Society,2003,12(7):729-739.
• [6]潘亦坚,林川,郭越,等.基于非经典感受野动态特性的轮廓检测模型[J].广西科技大学学报,2018,29(2):77-83.
• [7] MEHRANI P,MOURAVIEV A,GONZALEZ O J A,et al. Color-opponent mechanisms for local hue encoding in a hierarchi‐cal framework[J/OL].arXiv.org,2018(2)[2018-03-02]. http://cn.arxiv.org/pdf/1706.10266v2.
• [8]吴璟莉,刘袁静.一种基于颜色拮抗感受野的轮廓检测模型[J].计算机科学,2016,43(7):319-323.
• [9] MARTIN D R,FOWLKES C C,MALIK J. Learning to detect natural image boundaries using local brightness,color,and tex‐ture cues[J]. Transactions on Pattern Analysis and Machine Intelligence,2004,26(5):530-549.
• [10] MAIRE M,ARBELAEZ P,FOWLKES C,et al. Using contours to detect and localize junctions in natural images[C]//Usingcontours to detect and localize junctions in natural images. Computer Vision and Pattern Recognition,2008 CVPR 2008 IEEEConference.
• [11] ARBELAáEZ P,MAIRE M,FOWLKES C,et al. Contour detection and hierarchical image segmentation[C]//Contour Detec‐tion and Hierarchical Image Segmentation. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLI‐GENCE.
• [12] ZHOU C,MEL B W. Cue combination and color edge detection in natural scenes[J]. Journal of Vision,2008,8(4):1-25.
• [13] ZHANG J,BARHOMI Y,SERRE T. A new biologically inspired color image descriptor[C]//A New Biologically Inspired Col‐or Image Descriptor. European Conference on Computer Vision,312-324.
• [14] YANG K,GAO S,LI C,et al. Efficient color boundary detection with color-opponent mechanisms[C]//Efficient Color Bound‐ary Detection with Color-Opponent Mechanisms. IEEE Conference on Computer Vision and Pattern Recognition,2810-2817.
• [15] YANG K F,GAO S B,GUO C F,et al. Boundary detection using double-opponency and spatial sparseness constraint[J].IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society,2015,24(8):2565-2578.
• [16] LK P,WS B,R A,et al. Agenesis of the corpus callosum:genetic,developmental and functional aspects of connectivity[J]. Nature Reviews Neuroscience,2007,8(4):287-299.
• [17]杨开富.前端视觉通路信息加工的计算模型及应用研究[D].成都:电子科技大学,2016.
• [18] JOHNSON E N,HAWKEN M J,SHAPLEY R. The spatial transformation of color in the primary visual cortex of the macaquemonkey[J]. Nature Neuroscience,2001,4(4):409-416.
• [19] MARTIN D,FOWLKES C,TAL D,et al. A Database of Human Segmented Natural Images and its Application to EvaluatingSegmentation Algorithms and Measuring Ecological Statistics[C]//A Database of Human Segmented Natural Images and its Ap‐plication to Evaluating Segmentation Algorithms and Measuring Ecological Statistics. Computer Vision.

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