Online Submission!

Open Journal Systems

A NOVEL APPROACH TO SEGMENT LEAF REGION FROM PLANT LEAF IMAGE USING AUTOMATIC ENHANCED GRABCUT ALGORITHM

Jeyalakshmi S, R Radha

Abstract


Segmentation of leaf region from background is one of the essential pre-processing steps required in the Plant Leaf Image Processing.  This paper proposes an innovative segmentation approach for extracting color leaf region from the healthy or infected plant leaf image with background using an enhanced automatic GrabCut algorithm that does not take any input from the user. In this method, first GrabCut algorithm was applied on the original image. The algorithm removes background but shadows remain in the resultant image which may cause misinterpretations in further processing steps. Hence, the shadows in the image were removed by thresholding ‘a’ and ‘b’ components of CIELAB color space. This step created holes in the infected region, which had similar color as that of shadow, of the leaf image.  Hence, the image obtained was binarized and holes were filled with white (foreground) colorizing Flood Fill algorithm. From this binary image containing only leaf region, the color leaf region of the image was filtered. The accuracy achieved was 98%.

Keywords


Segmentation; Grab Cut; RGB Color Space; CIELAB Color space; Threshold; Flood Fill algorithm

Full Text:

PDF

References


Parviz Ahmadi Moghaddam, Mohammadali Haddad Derafshi and Vine Shirzad, “Estimation of Single Leaf Chlorophyll Content in Sugar Beet using Machine Vision”, Turk J Agric For Vol. 35, No. 6, (2011), pp. 563-568 © TÜBÍTAK, doi: 10.3906/tar-0909-393.

Satish Madhogaria, Marek Schikora, Wolfgang Koch, Daniel Cremers, “Pixel Based Classification for Detecting Unhealthy Regions in Leaf Images”, Proceedings of Informatikschaff Communities. pp. 1-11, 2011.

K. Dang, H. Sun, Jean-Pierre Chanet, J. Gracia-Vidal, J. M. Barcelo-Ordinas, H. L. Shi and K. M. Hou. “Wireless Multimedia Sensor Network for Plant Disease Detections”, Proceedings of New Information Communication Science and Technology for Sustainable Development: France-China International Workshop pp. 1-6 2013.

Marek Schikora, Adam Schikora, Karl-Heinz Kogel, Wolgang Kochi and Daniel Cremers. “Probabilistic Classification of Disease Symptoms caused by Salmonella on Arabidopsis Plants”, GI Jahrestagung Journal, Vol. 2, No. 10, pp. 874-879, 2010.

Marcelo Vassallo-Barco, Luis Vives-Garnique, Victor Tuesta-Monteza, Heber I. Mejia-Cabrera, Raciel Year Toledo, “Automatic Detection of Nutritional Deficiencies In Coffee Tree Leaves Through Shape and Texture Descriptor”, Journal of Digital Information Management, Vol.15, No.1 2017

Dina Khattab, Halamousher Ebied, Ashraf Saad Hussein AndMohamed FahmyTolba. “Color Image Segmentation Based on Different Color Space Models using Automatic Grabcut”, Hindawi Publishing Corporation, The Scientific World Journal Volume 2014, Article Id 126025, 10 Pages, http://dx.doi.org/ 10.1155/2014/126025

Michael Rzanny, Marco Seeland, Jana Walchen and Patrick Mader, “Acquiring And Preprocessing Leaf Images ForAutomated Plant Identification: Understanding The Tradeoff Between Effort And Information Gain”, Plant methods (2017) 13:97, DOI 10.1186/S 13007-017-0245-8.

Sun, J., Mao, H. and Yang, Y., “The Research on the Judgment of Paddy Rice’s Nitrogen Deficiency based on image”, 2009, in IFIP International Federation for Information processing, Volume 294, Computer and Computing Technologies in Agriculture II, Volume 2, eds. D. Li, S. Chunjiang, (Boston: Springer), pp. 1049-1054.

Sanjay B. Patil, Dr.Shrikant K. Bodhe. “Leaf Disease Severity Measurement using Image Processing”, International Journal of Engineering and Technology Vol. 3 (5), 2011, 297-301.

R. MeenaPrakash, G. P. Saraswathy, G. Ramalakshmi, K. H. Mangaleswari, T. Kaviya. “Detection of Leaf Diseases and Classification using Digital Image Processing”. 2017 International Conference on Innovations in Information, Embedded and Communication System (ICIIECS).

D. Preethi, Dr. D. Loganathan, “Image Assessment Metrics based on Distortion Measures”, International Journal of Engineering Science Invention (IJESI) ISSN(Online): 2319-6734, ISSN (Print): 2319-6726, PP. 52-58

Salomon, David (2007). “Data Compression: The Complete Reference (4 ed.)”, Springer-Verlag London pp.281, ISBN 978-1846286025

Eduardo Fernandez-Moral, Renato Martins, Denis Wolf, Patrick Rives. “A new metric for evaluating sematic segmentation: leveraging global and contour accuracy”, Workshop on Planning, Perception and Navigation for Intelligent Vehicles, PPNIV17, Sep 2017, Vancouver, Canada. Hal-01581525.

Images used in this research work were from the PlantVillage dataset (https://github.com/salathegroup/plantvillage-deeplearning-paper-dataset) (Last Accessed Date: 28-10-2019) licensed under Plant Village Dataset Creative Commons 3.0 Share and Share Alike

Manuel Grand-Brochier, Antoine Vacavant, GuillameCerutti, Camille Kurtz, Jonathan Weber Laure Tougne. “Tree Leaves Extraction in Natural Images: Comparative Study of preprocessing Tools and Segmentation Methods”. IEEE Transactions on image processing, Institute of Electrical and Electronics Engineers (IEEE), 2015, Vol. 24(5), pp.1549-1560.

https://www.sciencedirect.com/topics/engineering/color-matching-function (Last Accessed Date:15-09-2019).

Baisong Chen, Zhuo Fu, Yuchun Pan, Jihua Wang, and ZhixuanZeng.“Single Leaf Area Measurement Using Digital Camera Image”. CCTA 2010, Part II, IFIP AICT 345, pp. 525-530. 2011. © IFIP International Federation for Information Processing 2011.

https//www.colorcodehex.com/color-model.html (Last Accessed Date : 21-10-2019)

Sanjeev S Sannakki, Vijay S Rajpurohit and Sagar J Birje. “Comparison of Different Leaf Edge Detection Algorithms Using Fuzzy Mathematical Morphology”, International Journal of Innovations in Engineering and Technology (IJIET) Vol. 1 Issue 2 August 2012, pp. 15-21, ISSN: 2319 – 1058.

http://www.di.univr.it/documenti/OccorrenzaIns/matdid/matdid453675.pdf (Last Accessed Date: 28-10-2019)

Donald Hearn, M. Pauline Baker. “Computer Graphics – C Version”, Second Edition, 2006, pearson education Inc. and Dorling kindersley publisher Inc., Delhi, ISBN 978-81-7758-765-4.

Alain Horé and DjemelZiu. “Image quality metrics: PSNR vs. SSIM”, 2010 International Conference on Pattern Recognition, 1051-4651/10 © 2010 IEEE, DOI 10.1109/ICPR.2010.579

AkanshaTyagi, PriyaKumari and Dr. Mahesh Kumar Yadav. “Image Segmentation Techniques in DIP”, International Journal of Advanced Research Engineering Technology and Sciences, June 2016, Volume 3, Issue - 6 ISSN: 2394-2819

PitiAuearunyawat, TeerasitKasetkasem, AudthasitWongmaneeroj, Akinori Nishihara and RachapornKeinprasit. “An Automatic Nitrogen Estimation Method in Sugarcane Leaves Using Image Processing Techniques, International Conference on Agricultural, Environmental and Biological Sciences (ICAEBS’ 2012) May 26-27, 2012 Phuket.

PiyushChaudhary, Anand K. Chaudhari, Dr. A. N. Cheeran and ShardaGodara. “Color Transform Based Approach for Disease Spot Detection on Plant Leaf”, International Journal of Computer Science and Telecommunications Vol. 3, Issue 6, June 2012

http://cs.haifa.ac.il/hagit/courses/ist/Lectures/IST03_ColorXYZ.pdf (Last Accessed Date:28-10-2019)




DOI: http://dx.doi.org/10.6084/ijact.v8i11.995

Refbacks

  • There are currently no refbacks.




Copyright (c) 2019 COMPUSOFT: An International Journal of Advanced Computer Technology