{"title":"一种用于植物病害诊断的智能手机图像处理应用程序","authors":"N. Petrellis","doi":"10.1109/MOCAST.2017.7937683","DOIUrl":null,"url":null,"abstract":"Although professional agriculture engineers are responsible for the recognition of plant diseases, intelligent systems can be used for their diagnosis in early stages. The expert systems that have been proposed in the literature for this purpose, are often based on facts described by the user or image processing of plant photos in visible, infrared, light etc. The recognition of a disease can often be based on symptoms like lesions or spots in various parts of a plant. The color, area and the number of these spots can determine to a great extent the disease that has mortified a plant. Higher cost molecular analyses and tests can follow if necessary. A Windows Phone application is described here capable of recognizing vineyard diseases through photos of the leaves with an accuracy higher than 90%. This application can easily be extended for different plant diseases and different smart phone platforms.","PeriodicalId":202381,"journal":{"name":"2017 6th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"12 11","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"49","resultStr":"{\"title\":\"A smart phone image processing application for plant disease diagnosis\",\"authors\":\"N. Petrellis\",\"doi\":\"10.1109/MOCAST.2017.7937683\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Although professional agriculture engineers are responsible for the recognition of plant diseases, intelligent systems can be used for their diagnosis in early stages. The expert systems that have been proposed in the literature for this purpose, are often based on facts described by the user or image processing of plant photos in visible, infrared, light etc. The recognition of a disease can often be based on symptoms like lesions or spots in various parts of a plant. The color, area and the number of these spots can determine to a great extent the disease that has mortified a plant. Higher cost molecular analyses and tests can follow if necessary. A Windows Phone application is described here capable of recognizing vineyard diseases through photos of the leaves with an accuracy higher than 90%. This application can easily be extended for different plant diseases and different smart phone platforms.\",\"PeriodicalId\":202381,\"journal\":{\"name\":\"2017 6th International Conference on Modern Circuits and Systems Technologies (MOCAST)\",\"volume\":\"12 11\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"49\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 6th International Conference on Modern Circuits and Systems Technologies (MOCAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MOCAST.2017.7937683\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th International Conference on Modern Circuits and Systems Technologies (MOCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MOCAST.2017.7937683","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A smart phone image processing application for plant disease diagnosis
Although professional agriculture engineers are responsible for the recognition of plant diseases, intelligent systems can be used for their diagnosis in early stages. The expert systems that have been proposed in the literature for this purpose, are often based on facts described by the user or image processing of plant photos in visible, infrared, light etc. The recognition of a disease can often be based on symptoms like lesions or spots in various parts of a plant. The color, area and the number of these spots can determine to a great extent the disease that has mortified a plant. Higher cost molecular analyses and tests can follow if necessary. A Windows Phone application is described here capable of recognizing vineyard diseases through photos of the leaves with an accuracy higher than 90%. This application can easily be extended for different plant diseases and different smart phone platforms.