Application of UAV Image Detection Based on CBPSO Algorithm in Crop Pest Identification

Abstract

Bean is one of the widely grown crop in the world.This crop is easily prone to various diseases such as Alternaria alternata, Bacterial blight, Cercospora yellow spot and Red spider Mite.Among these diseases, spider mites are most dangerous and widely occurring disease, hence this paper mainly aims at classification and identification of spider mite disease caused by spider mite.These diseases cause damage to the plants by feeding on green content of leaf leading to aging and earliest fruitless end of the crop.In the existing situation farmer identify symptoms of the diseases by his vision, but he cannot differentiate types of the disease at its earliest stage of development.To know type of disease farmer need to get guidance from the expert which is time and cost fetching process.In order to control disease, it should be detected at its primary stage of development and pesticide is sprayed to the diseased plants.If the growth of disease extends its earliest stage of development, it cannot be controlled easily.In order to solve the problems faced by the existing system, a novel automated computer vision based system is proposed for classification and early detection of diseases on bean crop using image processing and sending diseased information to the farmer using mobile computing.The experiment is conducted over 400 images on the underside surface of leaves of bean crop.The Precision, Recall, Error Rate and Average Accuracy obtained by the proposed system in detecting red spider mite disease are 73.6%,81.2%, 15% and 84% respectively.

Plant phenotyping relevance

豆類葉の病害状態を画像から自動検出・分類するコンピュータビジョン手法が研究の中心であり、性能指標による評価も行われているため、植物病害フェノタイピング手法として採用する。

Code and data availability

The article describes a 400-image bean leaf dataset and MATLAB-based analysis, but contains no public deposit, availability statement, or URL for the dataset, images, or code. Only the publisher's site (ripublication.com) appears, which is not a paper-specific asset repository.

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