Analysis of informative feature changes on color images using mass-parallel processing

Remote sensing methods allow effective detecting field areas that are infected by plant diseases. The infection detected on early stages of its development reduces costs of plants protective measures. In the paper the problems of disease feature extraction as well as disease identification are considered. Three groups of potato plants with 25 images in each group were under experimental observation in laboratory conditions. The proposed algorithm of automatic definition of appearance i changes has shown good result of objects identification at use of an attribute of change of color characteristics of object. The greatest influence on job of a method renders: presence in the staff of extraneous subjects and the shadows, having color of object; non-uniformity of illumination that creates additional handicaps.

REFERENCES (11)

Belyaev B.I., Katkovsky L.V. Optical remote sensing. - Mińsk: BSU, 2006. - 455 p.

Google Scholar

N. Kumar, S. Pandey, A. Bhattacharya, and P. S. Ahuja, "Do leaf surface characteristics affect agrobacterium infection in tea [camellia sinensis (1.) o kuntze]?" J. Biosci., 2004. - Vol. 29, No. 3. - P. 309-317.

Google Scholar

P. Soille. Morphological image analysis applied to crop field mapping // Image and Vision Computing. - 2000. -Vol. 18, No. 13.-P. 1025-1032.

Google Scholar

Panagiotis Tzionas, Stelios E. Papadakis, Dimitris Manolakis. Plant leaves classification based on morphological features and a fuzzy surface selection technique // 5th Int. Conf. on Technology and Automation ICTA'05, 15-16 October 2005 Thessaloniki, Greece. -2005. - P. 365-370.

Google Scholar

Margarita Torre, Petia Radeva. Agricultural-Field Extraction on Aerial Images by Region Competition Algorithm // Int. Conf. on Pattern Recognition (ICPR'00), September 3-8, 2000, Barcelona, Spain. - 2000. - Vol. 01,No. l.-P. 1313-1316.

Google Scholar

A.V. Inyutin. The algorithm of image segmentation by grayscale pseudo-skeleton // Proc. of the III Int. Conf. on Neural Networks and Artificial Intelligence (ICNNAI 2003), November 12-14, Mińsk. Belarus. -2003. - P.263-265.

Google Scholar

Apan, Armando and Kelly, Rob and Jensen, Troy and Butler, David and Strong, Wayne and Basnet, Badri. Spectral Discrimination And Separability Analysis Of Agricultural Crops And Soil Attributes Using Aster Im-agery // In llth Australasian Remote Sensing and Photogrammetry Conference, 2-6 September, Brisbane, Queensland. - 2002. - P. 396-411.

Google Scholar

Burks, T.F., S.A. Shearer and F.A. Payne. Classification of weed species using color texture features and discriminant analysis // Transactions of ASAE. - 2000. -Vol. 43(2).-P. 441-448.

Google Scholar

Antonov S.A. Parallel programming using MPI / S. A. Antonov - Moscow, MSU, 2004. - 71 p. [In russian].

Google Scholar

10.

A. Petrovsky, A. Doudkin, V. Ganchenko, M. Vatkin. Potato detection using color leaves characteristics. // Pattern Recognition and Information Processing (PRIP'2007), May 22-24, Mińsk, Belarus, 2007. - P. 83-88.

Google Scholar

11.

Mitchell M., Advanced Linux Programming / Mark Mitchell, Jeffrey Oldham, Alex Samuel - Indianapolis: New Riders Publishing, 2001. - 368 p.

Google Scholar

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