Calculation of Texture Features for Polluted Leaves
Keywords:
Texture Features, Classification, Pollution, HistogramAbstract
This paper discuss about polluted leaves texture features. Texture analysis such as segmentation and classification plays a vital role in computer vision and pattern recognition and is widely applied to many areas such as industrial automation , bio-medical image processing and remote sensing. Now a day’s pollution is increasing day to day. classification of polluted leaves essential for some applications. To get the leaf based features image processing techniques are applied on the image of leaf. So texture features like mean, median ,skewness, kurtosis,GLCM and RMS of polluted leaves are published in this Article .Not only that Histogram of polluted leaves were published. Histograms of polluted leaves compared with data distribution measures like skewness and kurtosis.Manual polluted leafs identification task is time consuming process. Automatic detection of pollutant leaves is an active research topic now a days. Automatic polluted leaf identification will save time.In this paper histograms of nearly 30 polluted leafs of seven statistical measures were published.
References
Sumitra Giri ,”Effect of air pollution on chlorophyll content of leaves”,Current Agriculture Journal Vol,1(2),93-98(2013)
http://dx.doi.org/10.12944/CARJ.1.2.04
B.V Ramana Reddy A.Suresh Classification of Textures Based on Features Extracted from Preprocessing Images on Random Windows International Journal of Advanced Science and Technology Volume 9, August, 2009
A New Approach for Texture Segmentation Using Gray Level Textons International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 6, No. 3, June, 2013.
Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features Agric Eng Int: CIGR Journal Open access at http://www.cigrjournal.org Vol.15 No.1 211
Alireza Pourkhabbaz.Nayerah Rastin, “Influence of Environmental Pollution on leaf properties of urban plane trees,Platanus orientalis L.”, Bull Environ Contam Toxicol(2010)85:251-255,DOI 10.1007/s00128-010-0047-4 Busgenweg 1a,37077 Gottingen,Germany ,Springer 12 December 2009/Accepted:11 june 2010/Published online:25 june 2010.
University “Al.I.Cuza”Iasi , “Air Pollution Effects on the Leaf Structure of some Fabaceae Spacies”, Print ISSN 0255-965X;Electronic ISSN 1842-4309,Not.Bot.Hort.Agrobot.Cluj 37(2) 2009,57-63,Available online at www.notulaebotanicae.ro
Anett C.Hansen and Harald K.Selte,”Air Pollution and Sick-leaves –is there a connection? A Case study using Air Pollution Data from Oslo”,Discussion Papers No-197 Statistics Norway.july- 1997.
V.Venkata Krishna, “Classification of metals using texture features”, International Journal of Computer Science and Technology and Vol.4, Issue.spl-4, ISSN:0976-8491(online)/ISSN:2229-4333, 2013.
Revathi, P., and M. Hemalatha. "Cotton Leaf Spot Diseases Detection Utilizing Feature Selection with Skew Divergence Method." International Journal of Scientific Engineering and Technology (ISSN: 2277-1581) 3 (2014): 22-30.
Rastogi, A.; Arora, R.; Sharma, S., "Leaf disease detection and grading using computer vision technology & fuzzy logic," in Signal Processing and Integrated Networks (SPIN), 2015 2nd International Conference on , vol., no., pp.500-505, 19-20 Feb. 2015.
Classification of metals using texture features ,suneel kumar badugu ,venkata Krishna vakulabharanam et all IJCST IJCST Vol. 4, Iss ue Spl - 4, Oct - Dec 2013 , ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print).
Comparative study of various classification algorithms combined with K means algorithm for Leaf Identification International Journal Of Engineering And Computer Science ISSN: 2319-7242 Volume 5 Issues 6 June 2016, Page No. 17022-17025.
Abdul Kadir et all Leaf classification using shape,color,and texture features, International Journal of Computer Trends and Technology- July to Aug Issue 2011, ISSN: 2231-2803.
T. Acharya, & A.K. Ray, “Image Processingg Principles and Applications”, New Jersey: John Wiley & Sons, Inc, 2005 .
Y.A.O. Min, Y.I. Win-Sheng,S. Bin, &D.A.I. Hong-Hua, “An Image Retrieval System Based on Fractal Dimension”, Journal Zheijang University Science, vol. 4(4), p. 421-425, 2003. M. Petrou, & P.G. Sevilla, “Image Processing Dealing with Texture”, Chichester: John Wiley & Sons, Ltd., 2006.
M. Petrou, & P.G. Sevilla, “Image Processing Dealing with Texture”, Chichester: John Wiley & Sons, Ltd., 2006.
A. Gebejes, & Huertas, R. (2013). Texture Characterization Based on Grey-Level Co-Occurrence Matrix.
Studying the Kidney Textural Using Statistical Features and Local Binary Pattern Vol.20 (4), December, 2017, pp.64-76 Journal of Al-Nahrain University.
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.