Detection and Analysis of Deficiencies in Groundnut Plant using Geometric Moments
We propose our genuine research of geometric
moments which detects the mineral inadequacy in the frail groundnut
plant. This plant is prone to many deficiencies as a result of the
variance in the soil nutrients. By analyzing the leaves of the plant, we
detect the visual symptoms that are not recognizable to the naked eyes.
We have collected about 160 samples of leaves from the nearby fields.
The images have been taken by keeping every leaf into a black box to
avoid the external interference. For the first time, it has been possible
to provide the farmer with the stages of deficiencies. This paper has
applied the algorithms successfully to many other plants like Lady-s
finger, Green Bean, Lablab Bean, Chilli and Tomato. But we submit
the results of the groundnut predominantly. The accuracy of our
algorithm and method is almost 93%. This will again pioneer a kind of
green revolution in the field of agriculture and will be a boon to that
field.
[1] Economic and social impact of groundnut, Source: FAOSTAT, found at
URL:http://www.fao.org/fileadmin/user_upload/inpho/docs/Post_Harves
t_Compendium_Groundnut.pdf.
[2] Blumwald, E. (2003). Engineering salt tolerance in plants. Biotechnol.
Genet.eng.rev.20:261-275
[3] Braddy, N. C (1974) the nature and properties of soil, 8th edition,
Macmillan New York
[4] A. K. Jain and F. Farrokhnia, "Unsupervised Texture Segmentation Using
Gabor Filters," Pattern Recognition, vol. 24, pp. 1167-1186, 1991.
[5] T. Randen and J. H. Husoy, "Texture Segmentation Using Filters With
Optimized Energy Separation", IEEE Trans. on Image Processing, vol. 8,
pp. 571-582, 1999.
[6] M. M. Chang, M. I. Sezan, and A. M. Tekalp, "Adaptive Bayesian
Segmentation of Color Images", Journ. Of Electronic Imaging, vol. 3, pp.
404-414, 1994.
[7] Prof. Vilas Patil,"Effects of deficiencies on different cash crops", pp.
25-30,2000.
[8] D. Comaniciu and P. Meer, "Robust Analysis of Feature Spaces: Color
Image Segmentation", Proc. of IEEE Conf. Computer Vision and Pattern
Recognition, pp. 750-755, 1997.
[9] Y. Deng, B. S. Manjunath, "Unsupervised Segmentation of
Color-Texture Regions in Images and Video," IEEE Tr. PAMI, vol. 23,
pp. 800-810, 2001.
[10] Marijuana Plant Problems - Yellow Leave Brown Spots - Curly Leaves
found at URL:http://www.marijuana_seeds.net/Thanks_Thankyou.htm.
[11] G.C Gerloff, W.H Gabelman, "The Search for and Interpretation of
genetic controls that enhance Plant growth under nutrition levels of
Macronutrient", Plant soil. Volume.72, pp. 335
[12] Prof. Dr .Shindikar,"Study of Deficiencies in Tomato Plant Field
Survey" pp. 10-32, May-July (1998) .
[13] Boyce J.F. and Hossack W.J, "Moment invariants for pattern
recognition", Pattern Recognition Lett., Vol. 1, No. 5 (1983), pp. 451-456
[14] Kim W.Y,"A practical pattern recognition system for translation, scale
and rotation invariance", Intl. Conf. on Computer Vision and Pattern
Recgn,(1994),pp. 391-396.
[15] Gonzalez R.C. and Wintz P (Eds.), Digital Image Processing
(Addison-Wesley: Mass: 1987), pp. 419-423.
[16] Lin F and Brandt R.D.,"Towards absolute invariants of images under
translation, rotation, dilation", Pattern Recognition Lett., Vol. 14.No.
5(1993), pp. 369-379.
[17] Maitra S, "Moment Invariants",IEEE proceedings,Vol.67,No.4(1979),
pp.697-699.
[18] Philips W,"A new fast algorithm for moment computation", Pattern
Recognition, Vol. 26,No.11(1993), pp. 1619-1621.
[19] Sluzek A,"Identification and inspection of 2D objects using new momentbased
shape descriptors",Pattern Recognition Lett., No. 7(1995),
pp.687-697.
[20] Mukundan R, K. R. Ramakrishnan ,"Fast computation of Legendre and
Zernike Moments", Pattern Recognition, Vol. 28,No. 9,(Sep 1995),pp.
1433-1442.
[21] Mukundan, K. R. Ramakrishnan"Moment Functions in Image
Analysis"(1998), pp.1-5.
[22] Budrikis Z.L. and Hatamian M,"Moment calculation by digital filters",
AT&T Bell Lab Tech. Journal, Vol. 6,No. 2(1984), pp. 217-229.
[23] Chen K,"Efficient parallel algorithms for the computation of two
dimensional image moments",Pattern Recognition, Vol. 23, No. 1(1990),
pp. 109-119.
[1] Economic and social impact of groundnut, Source: FAOSTAT, found at
URL:http://www.fao.org/fileadmin/user_upload/inpho/docs/Post_Harves
t_Compendium_Groundnut.pdf.
[2] Blumwald, E. (2003). Engineering salt tolerance in plants. Biotechnol.
Genet.eng.rev.20:261-275
[3] Braddy, N. C (1974) the nature and properties of soil, 8th edition,
Macmillan New York
[4] A. K. Jain and F. Farrokhnia, "Unsupervised Texture Segmentation Using
Gabor Filters," Pattern Recognition, vol. 24, pp. 1167-1186, 1991.
[5] T. Randen and J. H. Husoy, "Texture Segmentation Using Filters With
Optimized Energy Separation", IEEE Trans. on Image Processing, vol. 8,
pp. 571-582, 1999.
[6] M. M. Chang, M. I. Sezan, and A. M. Tekalp, "Adaptive Bayesian
Segmentation of Color Images", Journ. Of Electronic Imaging, vol. 3, pp.
404-414, 1994.
[7] Prof. Vilas Patil,"Effects of deficiencies on different cash crops", pp.
25-30,2000.
[8] D. Comaniciu and P. Meer, "Robust Analysis of Feature Spaces: Color
Image Segmentation", Proc. of IEEE Conf. Computer Vision and Pattern
Recognition, pp. 750-755, 1997.
[9] Y. Deng, B. S. Manjunath, "Unsupervised Segmentation of
Color-Texture Regions in Images and Video," IEEE Tr. PAMI, vol. 23,
pp. 800-810, 2001.
[10] Marijuana Plant Problems - Yellow Leave Brown Spots - Curly Leaves
found at URL:http://www.marijuana_seeds.net/Thanks_Thankyou.htm.
[11] G.C Gerloff, W.H Gabelman, "The Search for and Interpretation of
genetic controls that enhance Plant growth under nutrition levels of
Macronutrient", Plant soil. Volume.72, pp. 335
[12] Prof. Dr .Shindikar,"Study of Deficiencies in Tomato Plant Field
Survey" pp. 10-32, May-July (1998) .
[13] Boyce J.F. and Hossack W.J, "Moment invariants for pattern
recognition", Pattern Recognition Lett., Vol. 1, No. 5 (1983), pp. 451-456
[14] Kim W.Y,"A practical pattern recognition system for translation, scale
and rotation invariance", Intl. Conf. on Computer Vision and Pattern
Recgn,(1994),pp. 391-396.
[15] Gonzalez R.C. and Wintz P (Eds.), Digital Image Processing
(Addison-Wesley: Mass: 1987), pp. 419-423.
[16] Lin F and Brandt R.D.,"Towards absolute invariants of images under
translation, rotation, dilation", Pattern Recognition Lett., Vol. 14.No.
5(1993), pp. 369-379.
[17] Maitra S, "Moment Invariants",IEEE proceedings,Vol.67,No.4(1979),
pp.697-699.
[18] Philips W,"A new fast algorithm for moment computation", Pattern
Recognition, Vol. 26,No.11(1993), pp. 1619-1621.
[19] Sluzek A,"Identification and inspection of 2D objects using new momentbased
shape descriptors",Pattern Recognition Lett., No. 7(1995),
pp.687-697.
[20] Mukundan R, K. R. Ramakrishnan ,"Fast computation of Legendre and
Zernike Moments", Pattern Recognition, Vol. 28,No. 9,(Sep 1995),pp.
1433-1442.
[21] Mukundan, K. R. Ramakrishnan"Moment Functions in Image
Analysis"(1998), pp.1-5.
[22] Budrikis Z.L. and Hatamian M,"Moment calculation by digital filters",
AT&T Bell Lab Tech. Journal, Vol. 6,No. 2(1984), pp. 217-229.
[23] Chen K,"Efficient parallel algorithms for the computation of two
dimensional image moments",Pattern Recognition, Vol. 23, No. 1(1990),
pp. 109-119.
@article{"International Journal of Biological, Life and Agricultural Sciences:60401", author = "Sumeet S. Nisale and Chandan J. Bharambe and Vidya N.More", title = "Detection and Analysis of Deficiencies in Groundnut Plant using Geometric Moments", abstract = "We propose our genuine research of geometric
moments which detects the mineral inadequacy in the frail groundnut
plant. This plant is prone to many deficiencies as a result of the
variance in the soil nutrients. By analyzing the leaves of the plant, we
detect the visual symptoms that are not recognizable to the naked eyes.
We have collected about 160 samples of leaves from the nearby fields.
The images have been taken by keeping every leaf into a black box to
avoid the external interference. For the first time, it has been possible
to provide the farmer with the stages of deficiencies. This paper has
applied the algorithms successfully to many other plants like Lady-s
finger, Green Bean, Lablab Bean, Chilli and Tomato. But we submit
the results of the groundnut predominantly. The accuracy of our
algorithm and method is almost 93%. This will again pioneer a kind of
green revolution in the field of agriculture and will be a boon to that
field.", keywords = "Component image, geometric moments, average
intensity, average affected area, black box", volume = "5", number = "10", pages = "620-5", }
