Survey paper on Identification and Classification of Plant Leaf Diseases

  • Yogesh Tambe
  • Amit Shinde
  • Vaibhav Tore
  • Sagar Bhandare

Abstract

The contribution of a plant is extremely vital for each human life and setting. Plants do suffer from diseases, like folks and animals. There’s the amount of plant diseases that occur and affects the conventional growth of a plant. These diseases have an effect on complete plant as well as leaf, stem, fruit, root, and flower. Most of the time once the illness of a plant has not been taken care of, the plant dies or might cause leaves drop, flowers and fruits drop etc. applicable diagnosing of such diseases is needed for correct identification and treatment of plant diseases. Plant pathology is that the study of plant diseases, their causes, procedures for dominant and managing them. But, the prevailing methodology encompasses human involvement for classification and identification of diseases. This procedure is long and expensive. Automatic segmentation of diseases from plant leaf pictures victimization soft computing approach is moderately helpful than the existing one. A technique named as bacterial foraging optimization based Radial Basis perform Neural Network (BRBFNN) for identification and classification of plant leaf diseases automatically. For distribution optimum weight to Radial Basis perform Neural Network (RBFNN) system use Bacterial forage optimization (BFO) that more will increase the speed and accuracy of the network to spot and classify the regions infected of various diseases on the plant leafs. The region growing algorithmic program increases the potency of the network by looking out and grouping of seed points having common attributes for feature extraction method.
Published
2019-04-09
How to Cite
TAMBE, Yogesh et al. Survey paper on Identification and Classification of Plant Leaf Diseases. International Journal Of Emerging Technology and Computer Science, [S.l.], v. 4, n. 2, p. 1-3, apr. 2019. ISSN 2455-9954. Available at: <https://aspirepublishers.com/index.php/ijetcs/article/view/258>. Date accessed: 22 apr. 2019.