Publication Type : Journal Article
Publisher : International Journal of Applied Engineering Research
Source : International Journal of Applied Engineering Research, Volume 10, Issue 55, 2015, Pages 1757-1761
Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942846683&partnerID=40&md5=1c50a19c96be869aae0af7f26b653a7c
Keywords : Image filtering, Segmentation, Template matching
Campus : Mysuru
School : School of Arts and Sciences
Department : Computer Science
Year : 2015
Abstract : Identification of fruit disease manually is a time consuming process. In this paper, an adaptive approach is proposed for the identification of fruit diseases and classification of fruit diseases. The proposed image processing based approach is composed of the following steps. In the first step, segmentation techniques are used in order to enhance the image, in the second step segmented images are used further for extracting the features using feature extraction methods and finally the images are classified. The proposed solution can significantly support accurate detection and classification of fruit disease which is helpful in horticulture field. © Research India Publications.
Cite this Research Publication : Pushpa, B.R., Tripulla, K.H., Meghana, T.K., "Detection and classification of fungal disease in fruits using image processing techniques", International Journal of Applied Engineering Research, 10 (55), pp. 1757-1761, 2015.