Enhancement of template-based method for overlapping rubber tree leaf identification

The automation rubber tree clone classification is subject of current researches.One of the feature to classify rubber clone is the position of rubber tree leaflets.These leaflets exist in three possible positions: overlapping, touching, or separated.Overlapping object recognition is one of the most difficult image processing task.Template matching method is proposed to identify overlapping leaflets. The position of rubber tree leaflets is one of the critical features for rubber clone classification. These leaflets exist in three possible positions: overlapping, touching, or separated. This paper proposed a template-based method for overlapping rubber tree leaf identification. Initially, the key point based feature extraction method is adopted. The key features of overlapping and non-overlapping leaf assist in identifying similar shapes through comparison, using the nearest neighbor algorithm. This process is implemented by constructing a directory which consists of various rubber leaf images with different positions. Next, the key points in the input leaf image are compared with the key points of the template image to identify the position of leaflets. The outcome of this study proves that the template-based method is suitable for overlapping and non-overlapping rubber tree leaf identification.

[1]  Carlos Caballero,et al.  WAPSI: Web Application for Plant Species Identification Using Fuzzy Image Retrieval , 2012, IPMU.

[2]  Johan A. K. Suykens,et al.  Sparse kernel spectral clustering models for large-scale data analysis , 2011, Neurocomputing.

[3]  Anju Bala.  An Improved Watershed Image Segmentation Technique using MATLAB , 2012 .

[4]  Matthew A. Brown,et al.  Automatic Panoramic Image Stitching using Invariant Features , 2007, International Journal of Computer Vision.

[6]  Seungmin Rho,et al.  Local feature-based multi-object recognition scheme for surveillance , 2012, Eng. Appl. Artif. Intell..

[7]  S. N. Geethalakshmi,et al.  Hybrid Image Segmentation Algorithm for Leaf Recognition and Characterization , 2011, 2011 International Conference on Process Automation, Control and Computing.

[8]  Ling Shao,et al.  Human action recognition based on boosted feature selection and naive Bayes nearest-neighbor classification , 2013, Signal Process..

[9]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[10]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Raúl Abella Pérez,et al.  An Incremental Text Segmentation by Clustering Cohesion , 2010 .

[12]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[13]  Soo-Chang Pei,et al.  Circular arc detection based on Hough transform , 1995, Pattern Recognit. Lett..

[14]  Laure Tougne,et al.  A Parametric Active Polygon for Leaf Segmentation and Shape Estimation , 2011, ISVC.

[15]  S. Anjomshoae.  A new feature extraction algorithm for overlapping leaves of rubber tree , 2014 .

[16]  S. N. Geethalakshmi,et al.  Plant Leaf Segmentation Using Non Linear K means Clustering , 2012 .

[17]  T. Kajisa,et al.  Importance of rubberwood in wood export of Malaysia and Thailand , 2011, New Forests.

[18]  Yu Ding,et al.  Segmentation, Inference and Classification of Partially Overlapping Nanoparticles , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Alfonso Caramazza,et al.  Overlapping representations for grip type and reach direction , 2014, NeuroImage.

[20]  Pallavi S. Gurjal,et al.  Real Time Hand Gesture Recognition Using Sift , 2012 .

[21]  Ghazali Sulong,et al.  Non-Linear Segmentation of Touched Roman Characters Based on Genetic Algorithm , 2010 .

[22]  Yangyang Li,et al.  Quantum evolutionary clustering algorithm based on watershed applied to SAR image segmentation , 2012, Neurocomputing.

[23]  Yu Qian,et al.  3D CBIR with sparse coding for image-guided neurosurgery , 2013, Signal Process..

[24]  S. Maurya,et al.  A semi automatic plant identification based on digital leaf and flower images , 2012, IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012).

[25]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[26]  Seong-Dae Kim,et al.  Scale-invariant template matching using histogram of dominant gradients , 2014, Pattern Recognit..

[27]  Hefei Ling,et al.  Fast image copy detection approach based on local fingerprint defined visual words , 2013, Signal Process..

[28]  Nasrul Humaimi Mahmood,et al.  Ultrasound liver image enhancement using watershed segmentation method , 2012 .

[29]  Knut-Andreas Lie,et al.  Automatic Segmentation of Overlapping Fish Using Shape Priors , 2007, SCIA.

[30]  Bin Lu,et al.  An Automatic Video Image Mosaic Algorithm Based on SIFT Feature Matching , 2013 .

[31]  Hae Yong Kim,et al.  Ciratefi: An RST-invariant template matching with extension to color images , 2011, Integr. Comput. Aided Eng..

[32]  Liang Zhao,et al.  Uncovering overlapping cluster structures via stochastic competitive learning , 2013, Inf. Sci..

[33]  Parvaneh Saeedi,et al.  Vision-based 3-D trajectory tracking for unknown environments , 2006, IEEE Transactions on Robotics.

[34]  Hong E Ren,et al.  An Algorithm of Leaf Image Segmentation Based on Color Features , 2011 .

[35]  Trond Melen,et al.  A Fast Algorithm for Dominant Point Detection on Chain-Coded Contours , 1993, CAIP.

[36]  Erkki Oja,et al.  A new curve detection method: Randomized Hough transform (RHT) , 1990, Pattern Recognit. Lett..

[37]  Shangsong Liang,et al.  Plant Species Classification Using Leaf Shape and Texture , 2012, 2012 International Conference on Industrial Control and Electronics Engineering.

[38]  Yu-Chiang Frank Wang,et al.  Moving foreground object detection via robust SIFT trajectories , 2013, J. Vis. Commun. Image Represent..

[39]  Yuanxin Ye,et al.  A local descriptor based registration method for multispectral remote sensing images with non-linear intensity differences , 2014 .

[40]  Muhammad Younus Javed,et al.  A hierarchical k-means clustering based fingerprint quality classification , 2012, Neurocomputing.