圆周特征描述:有效的叶片图像分类和检索方法
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摘要
叶片图像的识别是计算机视觉的一个重要应用,其关键问题是如何对其进行有效的描述.提出了一种圆周特征描述方法.该方法用圆心在轮廓线上的圆与轮廓线和叶片形状区域分别相交所得到的圆心角、区域点的空间分布和灰度统计,分别表征叶片的轮廓、形状区域和灰度信息这3类特征,称其为叶片图像的圆周特征描述.通过改变圆的半径来产生由粗到细的圆周特征描述,给出了一种局部的多尺度安排,根据圆心到轮廓线其他各点的距离信息,确定半径的取值范围和各个尺度的半径取值.该方法描述全面,通过分析圆周与叶片图像相交的几何特性,自然地抽取了叶片的轮廓线、区域和灰度信息,且描述子满足对相似性变换的不变性.在公开的测试集上,对该方法进行叶片的分类和检索实验,取得了比现有流行方法更高的精确度,验证了该方法的有效性.
Leaf image recognition is a significant application of computer vision. Its key issue is how to effectively describe the leaf images. A method, called circular features description, is proposed. In this method, a circular centered at the contour is put on the image plane and the central angle, the spatial distribution of the region points, and the gray statistics characteristics are derived from its intersection to the leaf contour and region for describing the contour, region and gray features of the leaf image. By varying the size of the circle, a coarse to fine descriptor is yielded and a local multiscale arrangement is developed in which the range of the radius of the circles and the values of various scales taking for each contour point are determined by the distance of the remaining contour points to it. The proposed method naturally integrates the contour, region, and grayscale information of the leaf image and is also invariant to the similarity transform of the leaf image. It is conducted on the public test datasets and the experimental results show its higher accuracies over the state-of-the-art methods.
Leaf image recognition is a significant application of computer vision. Its key issue is how to effectively describe the leaf images. A method, called circular features description, is proposed. In this method, a circular centered at the contour is put on the image plane and the central angle, the spatial distribution of the region points, and the gray statistics characteristics are derived from its intersection to the leaf contour and region for describing the contour, region and gray features of the leaf image. By varying the size of the circle, a coarse to fine descriptor is yielded and a local multiscale arrangement is developed in which the range of the radius of the circles and the values of various scales taking for each contour point are determined by the distance of the remaining contour points to it. The proposed method naturally integrates the contour, region, and grayscale information of the leaf image and is also invariant to the similarity transform of the leaf image. It is conducted on the public test datasets and the experimental results show its higher accuracies over the state-of-the-art methods.
引文
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[15]Liu M,Vemuri BC,Amari SI,Nielsen F.Shape retrieval using hierarchical total Bregman soft clustering.IEEE Trans.on Pattern Analysis&Machine Intelligence,2012,34(12):2407-2419.
[16]Du JX,Wang XF,Zhang GJ.Leaf shape based plant species recognition.Applied Mathematics and Computation,2007,185(2):883-893.
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[18]Wang XF,Huang DS,Du JX,et al.Classification of plant leaf images with complicated background.Applied Mathematics and Computation,2008,205(2):916-926.
[19]Horaisova K,Kukal J.Leaf classification from binary image via artificial intelligence.Biosystems Engineering,2016,142:83-100.
[20]Chaki J,Parekh R,Bhattacharya S.Plant leaf recognition using texture and shape features with neural classifiers.Pattern Recognition Letters,2015,58(1):61-68.
[21]Wu D,Yang H,Chen X,et al.Application of image texture for the sorting of tea categories using multi-spectral imaging technique and support vector machine.Journal of Food Engineering,2008,88(4):474-483.
[22]Casanova D,de Mesquita Sa Junior JJ,Bruno OM.Plant leaf identification using Gabor wavelets.Int’l Journal of Imaging Systems and Technology,2009,19(3):236-243.
[23]Tang Z,Su Y,Er MJ,et al.A local binary pattern based texture descriptors for classification of tea leaves.Neurocomputing,2015,168:1011-1023.
[24]Chen LX.Circular characteristics description:A method of plant leaf image recognition[MS.Thesis].Nanjing:Nanjing University of Finance and Economics,2016(in Chinese with English abstract).
[25]Aakif A,Khan MF.Automatic classification of plants based on their leaves.Biosystems Engineering,2015,139:66-75.
[26]Kalyoncu C,Toygar O.Geometric leaf classification.Computer Vision and Image Understanding,2015,133:102-109.
[27]Chang CC,Lin CJ.LIBSVM:A library for support vector machines.ACM Trans.on Intelligent Systems and Technology,2011,2:1-27.
[24]陈良宵.圆周特征描述:一种植物叶片图像识别方法[硕士学位论文].南京:南京财经大学,2016.
[2]Soderkvist O.Computer vision classification of leaves from Swedish trees[MS.Thesis].Linkoping:Linkoping University,2001.181-186.
[3]Cope JS,Corney D,Clark JY,et al.Plant species identification using digital morphometrics:A review.Expert Systems with Applications,2012,39(8):7562-7573.
[4]Belongie S,Malik J,Puzicha J.Shape matching and object recognition using shape contexts.IEEE Trans.on Pattern Analysis and Machine Intelligence,2002,24(4):509-522.
[5]Ling HB,Jacobs DW.Shape classification using the inner-distance.IEEE Trans.on Pattern Analysis and Machine Intelligence,2007,29(2):286-299.
[6]Zhao C,Chan SSF,Cham WK,et al.Plant identification using leaf shapes-A pattern counting approach.Pattern Recognition,2015,48:3203-3215.
[7]Wright J,Ma Y,Mairal J,Sapiro G,Huang TS,Yan S.Sparse representation for computer vision and pattern recognition.IEEEProc.,2010,98:1031-1044.
[8]Mokhtarian F,Mackworth AK.A theory of multiscale,curvature-based shape representation for planar curves.IEEE Trans.on Pattern Analysis and Machine Intelligence,1992,14(8):789-805.
[9]Alajlan N,El Rube,Kamel MS,et al.Shape retrieval using triangle-area representation and dynamic space warping.Pattern Recognition,2007,40(7):1912-1920.
[10]Mouine S,Yahiaoui I,Verroust-Blondet A.A shape-based approach for leaf classification using multiscale triangular representation.In:Proc.of the 3rd ACM Int’l Conf.on Multimedia Retrieval.2013.127-134.
[11]Manay S,Cremers D,Hong BW,et al.Integral invariants for shape matching.IEEE Trans.on Pattern Analysis and Machine Intelligence,2006,28(10):1602-1618.
[12]Kumar N,Belhumeur PN,Biswas A,et al.Leafsnap:A Computer Vision System for Automatic Plant Species Identification.Berlin,Heidelberg:Springer-Verlag,2012.502-516.
[13]Hu R,Jia W,Ling H,et al.Multiscale distance matrix for fast plant leaf recognition.IEEE Trans.on Image Processing,2012,21(11):4667-4672.
[14]Wang B,Brown D,Gao Y,et al.MARCH:Multiscale-arch-height description for mobile retrieval of leaf images.Information Sciences,2015,302:132-148.
[15]Liu M,Vemuri BC,Amari SI,Nielsen F.Shape retrieval using hierarchical total Bregman soft clustering.IEEE Trans.on Pattern Analysis&Machine Intelligence,2012,34(12):2407-2419.
[16]Du JX,Wang XF,Zhang GJ.Leaf shape based plant species recognition.Applied Mathematics and Computation,2007,185(2):883-893.
[17]Hu M.Visual pattern recognition by moment invariants.IRE Trans.on Information Theory,1962,8(2):179-187.
[18]Wang XF,Huang DS,Du JX,et al.Classification of plant leaf images with complicated background.Applied Mathematics and Computation,2008,205(2):916-926.
[19]Horaisova K,Kukal J.Leaf classification from binary image via artificial intelligence.Biosystems Engineering,2016,142:83-100.
[20]Chaki J,Parekh R,Bhattacharya S.Plant leaf recognition using texture and shape features with neural classifiers.Pattern Recognition Letters,2015,58(1):61-68.
[21]Wu D,Yang H,Chen X,et al.Application of image texture for the sorting of tea categories using multi-spectral imaging technique and support vector machine.Journal of Food Engineering,2008,88(4):474-483.
[22]Casanova D,de Mesquita Sa Junior JJ,Bruno OM.Plant leaf identification using Gabor wavelets.Int’l Journal of Imaging Systems and Technology,2009,19(3):236-243.
[23]Tang Z,Su Y,Er MJ,et al.A local binary pattern based texture descriptors for classification of tea leaves.Neurocomputing,2015,168:1011-1023.
[24]Chen LX.Circular characteristics description:A method of plant leaf image recognition[MS.Thesis].Nanjing:Nanjing University of Finance and Economics,2016(in Chinese with English abstract).
[25]Aakif A,Khan MF.Automatic classification of plants based on their leaves.Biosystems Engineering,2015,139:66-75.
[26]Kalyoncu C,Toygar O.Geometric leaf classification.Computer Vision and Image Understanding,2015,133:102-109.
[27]Chang CC,Lin CJ.LIBSVM:A library for support vector machines.ACM Trans.on Intelligent Systems and Technology,2011,2:1-27.
[24]陈良宵.圆周特征描述:一种植物叶片图像识别方法[硕士学位论文].南京:南京财经大学,2016.