| dc.description.abstract | Sri Lanka is well-known for its excellent TEA and as the 3rd largest tea manufacturing nation internationally. Sri Lanka is one of the main world’s top TEA exporters with a high global demand attracting millions of foreign exchanges, which strengthens the backbone of the economy of the country. Tea is grown in the whole country including central highlands and southern inland areas, resulting in a lot of diversity in the taste of Sri Lankan tea. Although TEA is an important agricultural field, the lack of attention, lack of resources, high cost of production has reduced its productivity and quality. One of the main reasons for this low productivity can be identified as tea leaf diseases due to changes in weather, infertile soil, pests, etc. This research paper suggests an automated and economical methodology to draw-up the current inefficient manual process of disease detection of tea leaves in tea cultivation by new trends of computing field such as image processing and machine learning techniques. The steps such as Image Acquisition, Image Segmentation, Image Pre-processing, Feature Exaction and Classification and Detection of tea leaf diseases are developed into an android application to provide effective, efficient, cost-effective and highly accurate system which will establish safer growing conditions. Also, the suggested solution will reduce the environmental and ecological impact due to usage of chemicals only in necessity to approved amounts to recommendations of the mobile application. | en_US |
